diff --git a/inference_benchmarks.md b/inference_benchmarks.md
index a12e1bc7..79487ee5 100644
--- a/inference_benchmarks.md
+++ b/inference_benchmarks.md
@@ -1,22 +1,23 @@
# Inference Benchmarks
-These tables collect inference benchmarks for Cosmos3. **Generator** sections measure visual-generation and world-model latency across PyTorch, vLLM-Omni, Diffusers, and NIM, including image and video generation, forward and inverse dynamics, and policy generation. **Reasoner** sections measure VLM serving and token-generation performance for text, image, and video inputs through vLLM and Hugging Face Transformers.
-
-Generator results are published incrementally from internal benchmark runs. **Empty cells mean that combination has not been measured yet** — not that it is unsupported. See the notes under each table for workload details and data-source definitions.
-
-## Table of Contents
-
-- [Cosmos3-Edge Generator](#cosmos3-edge-generator)
- - [vLLM-Omni](#vllm-omni)
- - [PyTorch](#pytorch)
-- [Cosmos3-Nano Generator](#cosmos3-nano-generator)
- - [Text-to-Video (t2v)](#text-to-video-t2v)
- - [Image-to-Video (i2v)](#image-to-video-i2v)
- - [Text-to-Image (t2i)](#text-to-image-t2i)
-- [Cosmos3-Super Generator](#cosmos3-super-generator)
- - [Text-to-Video (t2v)](#text-to-video-t2v-1)
- - [Image-to-Video (i2v)](#image-to-video-i2v-1)
- - [Text-to-Image (t2i)](#text-to-image-t2i-1)
+These reports collect inference benchmarks for Cosmos3. **Generator** pages measure image, video, audiovisual, and action-generation latency across PyTorch, vLLM-Omni, Diffusers, TensorRT-LLM, and NIM where results are available. **Reasoner** sections below measure VLM serving and token-generation performance for text, image, and video inputs through vLLM and Hugging Face Transformers.
+
+Results are published incrementally from internal benchmark runs. **Empty cells mean that combination has not been measured yet** — not that it is unsupported. See each model page or section for workload details and data-source definitions.
+
+## Generator benchmarks
+
+Generator results are organized by model so future checkpoints can be added without expanding this page into another wall of tables. Use the section links for modality-oriented navigation. The FP8 pages cover the quantized Nano and Super checkpoints; every other Generator page reports BF16, except NIM rows, which are FP8.
+
+| Model | Primary vision generation | Additional audiovisual generation | Transfer generation | Action generation |
+|---|---|---|---|---|
+| Cosmos3-Edge | [t2v, i2v, t2i](inference_benchmarks/cosmos3-edge-generator.md#text-to-video-t2v) | [v2v](inference_benchmarks/cosmos3-edge-generator.md#video-to-video-v2v) | Not reported | Not reported |
+| Cosmos3-Nano | [t2v, i2v, t2i](inference_benchmarks/cosmos3-nano-generator.md#primary-vision-generation) | [v2v, t2av, v2av, i2av](inference_benchmarks/cosmos3-nano-generator.md#additional-audiovisual-generation) | [blur, depth, edge, seg, wsm](inference_benchmarks/cosmos3-nano-generator.md#transfer-generation) | [Forward dynamics, inverse dynamics, policy](inference_benchmarks/cosmos3-nano-generator.md#action-generation) |
+| Cosmos3-Super | [t2v, i2v, t2i](inference_benchmarks/cosmos3-super-generator.md#primary-vision-generation) | [v2v, t2av, v2av, i2av](inference_benchmarks/cosmos3-super-generator.md#additional-audiovisual-generation) | [blur, depth, edge, seg, wsm](inference_benchmarks/cosmos3-super-generator.md#transfer-generation) | [Forward dynamics, inverse dynamics, policy](inference_benchmarks/cosmos3-super-generator.md#action-generation) |
+| Cosmos3-Nano-FP8 | [t2v, i2v, t2i](inference_benchmarks/cosmos3-nano-fp8-generator.md#primary-vision-generation) | [v2v, t2av, v2av, i2av](inference_benchmarks/cosmos3-nano-fp8-generator.md#additional-audiovisual-generation) | [blur, depth, edge, multi_control, seg, wsm](inference_benchmarks/cosmos3-nano-fp8-generator.md#transfer-generation) | [Forward dynamics, inverse dynamics, policy](inference_benchmarks/cosmos3-nano-fp8-generator.md#action-generation) |
+| Cosmos3-Super-FP8 | [t2v, i2v, t2i](inference_benchmarks/cosmos3-super-fp8-generator.md#primary-vision-generation) | [v2v, t2av, v2av, i2av](inference_benchmarks/cosmos3-super-fp8-generator.md#additional-audiovisual-generation) | [blur, depth, edge, multi_control, seg, wsm](inference_benchmarks/cosmos3-super-fp8-generator.md#transfer-generation) | [Forward dynamics, inverse dynamics, policy](inference_benchmarks/cosmos3-super-fp8-generator.md#action-generation) |
+
+## Reasoner benchmarks
+
- [Cosmos3-Edge Reasoner](#cosmos3-edge-reasoner)
- [RTX PRO 4500 Blackwell Server Edition](#rtx-pro-4500-blackwell-server-edition)
- [RTX PRO 6000 Blackwell Server Edition](#rtx-pro-6000-blackwell-server-edition)
@@ -39,290 +40,6 @@ Generator results are published incrementally from internal benchmark runs. **Em
- [B200](#b200-1)
- [B300](#b300-1)
-## Cosmos3-Edge Generator
-
-These tables report **Cosmos3-Edge** Generator latency in seconds for **image-to-video (i2v)**. Measurements use one GPU or one integrated computing platform. Lower latency is better, and empty cells indicate that a run has not been completed.
-
-Unless otherwise noted, visual-generation benchmarks use **480p resolution**. Video benchmarks generate **121 frames**. vLLM-Omni values report end-to-end latency, while PyTorch values report average generation latency.
-
-### vLLM-Omni
-
-| GPU or Platform | Image-to-Video |
-|---|---:|
-| B200 SXM 192 GB | 7.09 |
-| B300 | 8.74 |
-| H200 SXM 141 GB | 13.13 |
-| H200 NVL | 14.15 |
-| H100 SXM 80 GB | 13.33 |
-| H100 NVL 96 GB | 17.33 |
-| H20 SXM 96 GB | 53.94 |
-| RTX PRO 6000 Blackwell Server Edition | |
-| DGX Station | 7.13 |
-| DGX Spark | 89.41 |
-| Jetson AGX Thor T5000, 128 GB, MAXN | |
-| Jetson T3000, 32 GB, 1100 MHz | |
-| Jetson T2000, 16 GB, 702 MHz, THOR_NANO | |
-
-### PyTorch
-
-| GPU or Platform | Image-to-Video |
-|---|---:|
-| B200 SXM 192 GB | 7.45 |
-| B300 | 6.84 |
-| H200 SXM 141 GB | 12.31 |
-| H200 NVL | 14.07 |
-| H100 SXM 80 GB | 12.68 |
-| H100 NVL 96 GB | 16.42 |
-| H20 SXM 96 GB | 52.83 |
-| RTX PRO 6000 Blackwell Server Edition | 21.92 |
-| DGX Station | 6.31 |
-| DGX Spark | 103.36 |
-| Jetson AGX Thor T5000, 128 GB, MAXN | |
-| Jetson T3000, 32 GB, 1100 MHz | |
-
-Notes:
-1. All measurements use one GPU or one integrated computing platform.
-2. Values are average end-to-end or generation latency in seconds; lower is better.
-3. Unless otherwise specified, visual-generation measurements use **480p resolution**.
-4. Video measurements (i2v) generate **121 output frames**.
-5. PyTorch values report average generation latency rather than diffusion-only latency.
-
-## Cosmos3-Nano Generator
-
-These tables report **Cosmos3-Nano** generator latency in seconds for **image-to-video (i2v)**, **text-to-image (t2i)**, and **text-to-video (t2v)** - the primary vision-generation modes of the omni-model. Benchmarks use BF16 precision, batch size 1, and identical prompts, seeds, and sampler settings across engines where noted below. Video workloads follow the standard Cosmos3 generation profile (189 frames at 24 FPS unless a resolution tier limits frame count).
-
-Four integration paths are compared. **PyTorch** reports average generation (sampling) time from OSS reference inference with CUDA Graphs enabled where supported. **vLLM-Omni** reports total pipeline time at **720p** on supported GPUs. **Diffusers** reports end-to-end generation time through the Hugging Face `Cosmos3OmniPipeline` without custom CUDA graphs at **256p/1**, **480p/1**, and **720p/1** (320×192, 832×480, and 1280×720). **NIM** reports end-to-end request latency using NIM latency profiles with FP8 precision, including request processing, video generation, output encoding, and returning the response. Empty cells indicate a run has not been completed for that GPU, engine, resolution, or tensor-parallel width - tables are filled in as benchmark campaigns finish.
-
-### Text-to-Video (t2v)
-
-| GPU | Engine | 256p/1 | 256p/4 | 256p/8 | 480p/1 | 480p/4 | 480p/8 | 720p/1 | 720p/4 | 720p/8 |
-|---|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|
-| **RTX PRO 6000 Blackwell** | PyTorch | 13.95 | | 4.90 | 180.81 | | | 786.37 | 225.45 | 127.57 |
-| | vLLM-Omni | 10.65 | 5.06 | 3.78 | 105.61 | 35.93 | 23.76 | 369.67 | 114.30 | 68.66 |
-| | Diffusers | 11.20 | | | 112.00 | | | 392.00 | | |
-| | NIM | 7.93 | 4.69 | 4.00 | 82.69 | 33.57 | 24.49 | 318.69 | 107.83 | 68.50 |
-| **H20** | PyTorch | 30.57 | | | 257.51 | | | 931.39 | 268.88 | 157.71 |
-| | vLLM-Omni | 28.58 | 10.20 | 7.70 | 256.97 | 77.42 | 47.53 | 929.81 | 260.75 | 148.46 |
-| | Diffusers | 30.20 | | | 258.00 | | | 926.00 | | |
-| | NIM | 17.81 | 7.84 | 6.14 | 192.07 | 62.80 | 41.67 | 771.37 | 223.24 | 132.68 |
-| **H100 NVL** | PyTorch | 10.03 | 4.27 | 3.95 | 84.12 | 29.18 | 21.46 | 297.27 | 94.15 | 61.63 |
-| | vLLM-Omni | 9.25 | 3.68 | 3.15 | 80.75 | 27.48 | 18.77 | 311.13 | 88.25(*) | 54.01(*) |
-| | Diffusers | 11.00 | | | 90.00 | | | 324.20 | | |
-| | NIM | 7.09 | 3.77 | 3.65 | 68.01 | 25.67 | 20.51 | 267.73 | 86.18 | 57.38 |
-| **H200 NVL** | PyTorch | 8.17 | | | 69.79 | | | 244.39 | 77.35 | 45.70 |
-| | vLLM-Omni | 7.44 | 3.27 | 2.33 | 64.58 | 21.31 | 12.92 | 240.05 | 69.63 | 39.17 |
-| | Diffusers | 9.00 | | | 74.00 | | | 276.20 | | |
-| | NIM | 5.87 | 3.38 | 3.00 | 57.10 | 21.74 | 15.04 | 229.63 | 71.32 | 43.34 |
-| **H100 80GB HBM3** | PyTorch | 7.61 | 3.50 | 3.17 | 59.83 | 21.23 | 14.37 | 207.78 | 66.94 | 41.81 |
-| | vLLM-Omni | 6.97 | 3.45 | 3.49 | 58.17 | 19.95 | 13.46 | 202.29 | 62.82 | 37.80 |
-| | Diffusers | 9.00 | | | 68.00 | | | 240.00 | | |
-| | NIM | 5.72 | 3.36 | 3.12 | 51.73 | 20.26 | 14.82 | 199.46 | 65.32 | 41.66 |
-| **H200 141GB HBM3** | PyTorch | 7.53 | 3.34 | 3.19 | 60.18 | 20.84 | 13.97 | 214.28 | 67.48 | 41.26 |
-| | vLLM-Omni | 6.79 | 3.25 | 3.42 | 58.14 | 19.77 | 12.97 | 208.36 | 63.27 | 37.49 |
-| | Diffusers | 9.00 | | | 67.00 | | | 239.60 | | |
-| | NIM | 5.72 | 3.26 | 3.10 | 51.90 | 20.09 | 14.61 | 200.63 | 64.57 | 40.70 |
-| **B200** | PyTorch | 4.56 | 2.78 | 2.79 | 33.20 | 13.20 | 9.69 | 114.85 | 39.75 | 26.27 |
-| | vLLM-Omni | 4.03 | 2.43 | 3.49 | 32.04 | 12.63 | 10.09 | 107.84 | 35.29 | 22.87 |
-| | Diffusers | 7.00 | | | 36.80 | | | 117.00 | | |
-| | NIM | 3.72 | 2.74 | 2.89 | 26.68 | 12.66 | 10.10 | 93.33 | 35.04 | 24.64 |
-| **B300** | PyTorch | | | | | | | | | |
-| | vLLM-Omni | 4.46 | 4.11 | 5.44 | 32.18 | 13.83 | 11.57 | 102.10 | 35.68 | 24.33 |
-| | Diffusers | 39.40 | | | 63.40 | | | 139.40 | | |
-| | NIM | 4.51 | 3.54 | 4.11 | 27.49 | 14.51 | 11.86 | 90.39 | 37.28 | 26.19 |
-
-### Image-to-Video (i2v)
-
-| GPU | Engine | 256p/1 | 256p/4 | 256p/8 | 480p/1 | 480p/4 | 480p/8 | 720p/1 | 720p/4 | 720p/8 |
-|---|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|
-| **RTX PRO 6000 Blackwell** | PyTorch | | | | 182.14 | | | 788.80 | 226.25 | 127.79 |
-| | vLLM-Omni | 11.04 | 5.48 | 4.24 | 107.77 | 38.05 | 25.95 | 375.01 | 119.27 | 73.57 |
-| | Diffusers | 12.00 | | | 112.00 | | | 397.00 | | |
-| | NIM | 8.23 | 5.28 | 4.64 | 84.58 | 35.74 | 26.63 | 326.96 | 112.27 | 73.31 |
-| **H20** | PyTorch | 31.36 | | | 257.10 | | | 933.07 | 268.99 | 158.10 |
-| | vLLM-Omni | 29.50 | 11.26 | 8.64 | 261.56 | 81.93 | 52.06 | 940.16 | 271.37 | 158.76 |
-| | Diffusers | 31.00 | | | 258.00 | | | 925.00 | | |
-| | NIM | 18.67 | 9.04 | 7.38 | 195.10 | 67.64 | 46.30 | 774.88 | 233.92 | 143.15 |
-| **H100 NVL** | PyTorch | 10.19 | 4.31 | 3.99 | 84.50 | 28.69 | 21.52 | 298.57 | 95.76 | 60.58 |
-| | vLLM-Omni | 9.62 | 4.11 | 3.63 | 82.61 | 29.35 | 20.73 | 286.33 | 92.23(*) | 58.02(*) |
-| | Diffusers | 11.00 | | | 91.00 | | | 325.20 | | |
-| | NIM | 7.39 | 4.36 | 4.28 | 69.39 | 27.67 | 22.43 | 272.29 | 90.26 | 61.55 |
-| **H200 NVL** | PyTorch | 8.27 | | | 69.99 | | | 246.62 | 77.69 | 45.99 |
-| | vLLM-Omni | 7.83 | 3.69 | 2.78 | 66.39 | 22.93 | 14.58 | 243.52 | 73.26 | 42.86 |
-| | Diffusers | 9.00 | | | 74.00 | | | 275.20 | | |
-| | NIM | 6.25 | 3.97 | 3.60 | 58.64 | 23.33 | 16.75 | 232.47 | 75.13 | 47.22 |
-| **H100 80GB HBM3** | PyTorch | 7.64 | 3.47 | 3.21 | 59.95 | 21.40 | 14.43 | 207.87 | 67.52 | 41.66 |
-| | vLLM-Omni | 7.37 | 3.81 | 3.97 | 59.77 | 21.68 | 15.12 | 205.97 | 66.52 | 41.51 |
-| | Diffusers | 9.00 | | | 68.00 | | | 239.80 | | |
-| | NIM | 6.08 | 3.89 | 3.71 | 53.02 | 22.20 | 16.61 | 202.59 | 69.02 | 45.16 |
-| **H200 141GB HBM3** | PyTorch | 7.65 | 3.37 | 3.17 | 60.51 | 21.01 | 14.07 | 214.80 | 67.14 | 41.00 |
-| | vLLM-Omni | 7.28 | 3.63 | 3.83 | 59.64 | 21.35 | 14.67 | 209.65 | 66.65 | 40.77 |
-| | Diffusers | 9.00 | | | 67.20 | | | 240.00 | | |
-| | NIM | 6.04 | 3.80 | 3.65 | 53.25 | 21.89 | 16.23 | 203.66 | 68.30 | 44.29 |
-| **B200** | PyTorch | 4.60 | 2.77 | 2.81 | | 13.07 | 9.66 | 113.90 | 40.01 | 26.58 |
-| | vLLM-Omni | 4.33 | 2.77 | 3.84 | 33.09 | 13.79 | 11.39 | 110.19 | 37.76 | 25.68 |
-| | Diffusers | | | | | | | 116.00 | | |
-| | NIM | 4.05 | 3.43 | 3.60 | 27.72 | 14.02 | 11.43 | 95.57 | 37.76 | 27.29 |
-| **B300** | PyTorch | | | | | | | | | |
-| | vLLM-Omni | 5.61 | 4.67 | 5.90 | 33.45 | 15.06 | 13.13 | 104.75 | 38.27 | 26.87 |
-| | Diffusers | 28.60 | | | 65.60 | | | 139.60 | | |
-| | NIM | 4.50 | 4.96 | 5.03 | 28.90 | 16.06 | 13.25 | 92.59 | 39.49 | 29.00 |
-
-### Text-to-Image (t2i)
-
-| GPU | Engine | 256p/1 | 256p/4 | 256p/8 | 480p/1 | 480p/4 | 480p/8 | 720p/1 | 720p/4 | 720p/8 |
-|---|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|
-| **RTX PRO 6000 Blackwell** | PyTorch | 2.99 | | | 4.51 | | | 7.12 | 3.18 | 2.70 |
-| | vLLM-Omni | 1.59 | 1.54 | 1.59 | 2.87 | 1.55 | 1.81 | 4.99 | 2.32 | 1.96 |
-| | Diffusers | 2.00 | | | 4.00 | | | 5.00 | | |
-| **H20** | PyTorch | 3.06 | | | 6.51 | | | 12.31 | 4.28 | 3.06 |
-| | vLLM-Omni | 1.73 | 2.46 | 3.22 | 4.92 | 2.57 | 7.24 | 10.73 | 4.24 | 3.59 |
-| | Diffusers | 3.00 | | | 6.00 | | | 10.00 | | |
-| **H100 NVL** | PyTorch | 2.77 | 2.45 | 2.57 | 2.83 | 2.56 | 2.51 | 4.21 | 2.57 | 2.64 |
-| | vLLM-Omni | 1.55 | 1.75 | 1.91 | 1.92 | 1.81 | 10.82 | 3.44 | 1.83 | 1.90 |
-| | Diffusers | 3.00 | | | 3.00 | | | 4.00 | | |
-| **H200 NVL** | PyTorch | | | | 2.85 | | | 3.58 | 2.62 | 2.64 |
-| | vLLM-Omni | 1.53 | 2.01 | 1.96 | 1.58 | 1.91 | 17.71 | 2.81 | 1.94 | 1.94 |
-| | Diffusers | 3.00 | | | 3.00 | | | 4.00 | | |
-| **H100 80GB HBM3** | PyTorch | 3.01 | 2.66 | 2.56 | 3.01 | 2.59 | 2.75 | 3.45 | 2.73 | 2.77 |
-| | vLLM-Omni | 1.61 | 2.45 | 3.18 | 1.53 | 2.35 | 7.02 | 2.61 | 2.45 | 3.03 |
-| | Diffusers | 3.00 | | | 3.00 | | | 4.00 | | |
-| **H200 141GB HBM3** | PyTorch | 2.96 | 2.59 | 2.70 | 3.04 | 2.78 | 2.77 | 3.28 | 2.84 | 2.77 |
-| | vLLM-Omni | 1.57 | 2.38 | 3.16 | 1.52 | 2.37 | 7.05 | 2.60 | 2.33 | 3.20 |
-| | Diffusers | 3.00 | | | 3.00 | | | 4.00 | | |
-| **B200** | PyTorch | | 2.39 | 2.59 | 2.75 | 2.43 | 2.56 | 2.87 | 2.58 | 2.62 |
-| | vLLM-Omni | 1.49 | 2.21 | 3.27 | 1.20 | 2.05 | 7.58 | 1.77 | 2.20 | 3.41 |
-| | Diffusers | | | | | | | 3.00 | | |
-| **B300** | PyTorch | | | | | | | | | |
-| | vLLM-Omni | 1.97 | 4.52 | 5.82 | 1.81 | 4.16 | 71.19 | 2.34 | 4.09 | 5.62 |
-| | Diffusers | 36.20 | | | | | | 41.00 | | |
-
-Notes:
-1. All times measured on identical workloads (same seed, sampler settings, prompt).
-2. 4×/8× GPU configurations use tensor parallelism.
-3. vLLM-Omni numbers are for the upcoming public release in the vLLM-Omni repo; subject to change before GA. Values marked with (*) are pre-release vLLM-Omni measurements on H100 NVL and may change before GA.
-4. Diffusers numbers use the HuggingFace `diffusers` integration without custom CUDA graphs; reported at 256p/1, 480p/1, and 720p/1 (single-GPU only).
-5. PyTorch numbers report average generation (sampling) time from OSS inference benchmarking.
-6. At 256p, multi-GPU configurations on B300 may underperform single-GPU due to small-workload TP overhead; single-GPU is recommended at this resolution.
-7. NIM numbers use latency profiles with FP8 precision and report end-to-end `Request Latency s`, including request processing, video generation, output encoding, and returning the response.
-
-## Cosmos3-Super Generator
-
-These tables report **Cosmos3-Super** generator latency in seconds for **image-to-video (i2v)**, **text-to-image (t2i)**, and **text-to-video (t2v)**. The 32B checkpoint targets higher-quality world generation; expect longer runtimes than Nano at the same resolution. Benchmarks use BF16 precision, batch size 1, and matched prompts, seeds, and sampler settings. Video workloads follow the standard Cosmos3 profile (189 frames at 24 FPS where applicable).
-
-As with Nano, four engines are tracked: **PyTorch** (OSS generation/sampling time), **vLLM-Omni** (total pipeline time at 720p on supported GPUs), **Diffusers** (Hugging Face `Cosmos3OmniPipeline` end-to-end time at **256p/1**, **480p/1**, and **720p/1** — 320×192, 832×480, and 1280×720), and **NIM** (end-to-end request latency using latency profiles with FP8 precision, including request processing, video generation, output encoding, and returning the response). Super coverage is narrower than Nano in early releases - for example, vLLM-Omni and Diffusers runs exist primarily on B200 and select H200 configurations. **Empty cells are pending measurements**, not unsupported configurations.
-
-### Text-to-Video (t2v)
-
-| GPU | Engine | 256p/1 | 256p/4 | 256p/8 | 480p/1 | 480p/4 | 480p/8 | 720p/1 | 720p/4 | 720p/8 |
-|---|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|
-| **RTX PRO 6000 Blackwell** | PyTorch | | | | | | | | 789.03 | 427.16 |
-| | vLLM-Omni | | | | | | | | | |
-| | Diffusers | | | | | | | | | |
-| | NIM | | 12.65 | 13.99 | | 104.25 | 99.05 | | 350.74 | 286.02 |
-| **H20** | PyTorch | | | | | | | | | 492.41 |
-| | vLLM-Omni | | | | | | | | | |
-| | Diffusers | | | | | | | | | |
-| | NIM | | 20.07 | 12.95 | | 192.45 | 110.71 | | 734.37 | 395.56 |
-| **H100 NVL** | PyTorch | | | 16.83 | | 101.27 | 64.14 | | 330.04 | 186.19 |
-| | vLLM-Omni | | | | | | | | | |
-| | Diffusers | | | | | | | | | |
-| | NIM | | 8.77 | 12.73 | | 73.37 | 66.07 | | 267.64 | 197.32 |
-| **H200 NVL** | PyTorch | | | | | | | | 258.34 | 139.37 |
-| | vLLM-Omni | 27.54 | | 5.06 | 252.33 | | 36.66 | 911.49 | 245.51 | 123.85 |
-| | Diffusers | 33.00 | | | 286.80 | | | 1036.00 | | |
-| | NIM | 17.13 | 6.79 | 4.43 | 200.00 | 58.55 | 32.87 | 811.41 | 223.00 | 117.98 |
-| **H100 80GB HBM3** | PyTorch | | | | | | | | | |
-| | vLLM-Omni | | | | | | | | | |
-| | Diffusers | | | | | | | | | |
-| | NIM | | 6.98 | 5.89 | | 55.10 | 35.52 | | 198.13 | 114.92 |
-| **H200 141GB HBM3** | PyTorch | | 14.82 | 11.82 | | 70.27 | 41.78 | | 224.43 | 123.49 |
-| | vLLM-Omni | 25.61 | | 5.87 | 219.11 | | 35.26 | 769.63 | 212.30 | 111.94 |
-| | Diffusers | 31.00 | | | 251.60 | | | 886.20 | | |
-| | NIM | 15.95 | 6.14 | 4.28 | 174.71 | 52.94 | 30.94 | 695.89 | 194.34 | 106.16 |
-| **B200** | PyTorch | | 5.59 | 4.09 | 114.38 | 35.73 | 21.39 | 407.50 | 118.38 | 65.93 |
-| | vLLM-Omni | 13.84 | | 4.76 | 114.08 | | 22.09 | 390.28 | 113.31 | 62.11 |
-| | Diffusers | | | | 127.20 | | | 414.40 | | |
-| | NIM | 9.09 | 4.26 | 3.38 | 82.39 | 27.83 | 17.74 | 314.68 | 92.25 | 53.43 |
-| **B300** | PyTorch | | | | | | | | | |
-| | vLLM-Omni | 14.57 | | 6.68 | 109.03 | | 22.67 | 366.66 | 108.58 | 60.73 |
-| | Diffusers | 54.20 | | | 155.40 | | | 424.80 | | |
-| | NIM | 9.67 | 5.23 | 5.19 | 79.73 | 28.97 | 18.39 | 292.35 | 92.31 | 54.07 |
-
-### Image-to-Video (i2v)
-
-| GPU | Engine | 256p/1 | 256p/4 | 256p/8 | 480p/1 | 480p/4 | 480p/8 | 720p/1 | 720p/4 | 720p/8 |
-|---|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|
-| **RTX PRO 6000 Blackwell** | PyTorch | | | | | | | | 795.14 | 427.96 |
-| | vLLM-Omni | | | | | | | | | |
-| | Diffusers | | | | | | | | | |
-| | NIM | | 13.17 | 14.48 | | 106.50 | 100.23 | | 356.60 | 289.93 |
-| **H20** | PyTorch | | | | | | | | 931.74 | |
-| | vLLM-Omni | | | | | | | | | |
-| | Diffusers | | | | | | | | | |
-| | NIM | | 21.16 | 14.06 | | 196.86 | 114.49 | | 745.12 | 405.68 |
-| **H100 NVL** | PyTorch | | 20.85 | 16.96 | | 99.56 | | | 331.40 | 186.47 |
-| | vLLM-Omni | | | | | | | | | |
-| | Diffusers | | | | | | | | | |
-| | NIM | | 9.32 | 13.30 | | 75.31 | 67.34 | | 271.46 | 201.39 |
-| **H200 NVL** | PyTorch | | | | | | | | 265.33 | 138.31 |
-| | vLLM-Omni | 27.90 | | 5.52 | 254.29 | | 38.51 | 915.05 | 248.89 | 127.32 |
-| | Diffusers | 33.00 | | | 287.20 | | | 1034.60 | | |
-| | NIM | 17.51 | 7.43 | 5.04 | 201.45 | 60.15 | 34.48 | 817.35 | 226.38 | 121.35 |
-| **H100 80GB HBM3** | PyTorch | | | | | | | | | |
-| | vLLM-Omni | | | | | | | | | |
-| | Diffusers | | | | | | | | | |
-| | NIM | | 7.50 | 6.49 | | 56.33 | 36.81 | | 200.97 | 118.77 |
-| **H200 141GB HBM3** | PyTorch | | 14.87 | 11.80 | | 70.45 | 42.10 | | 224.36 | 123.57 |
-| | vLLM-Omni | 25.47 | | 6.32 | 220.70 | | 36.90 | 766.33 | 215.03 | 117.52 |
-| | Diffusers | 31.00 | | | 249.20 | | | 879.20 | | |
-| | NIM | 16.39 | 6.74 | 4.90 | 175.95 | 54.46 | 32.51 | 699.13 | 197.96 | 109.55 |
-| **B200** | PyTorch | 14.71 | 5.63 | 4.12 | | 35.70 | 21.25 | 397.31 | 117.98 | 65.91 |
-| | vLLM-Omni | 14.13 | | 5.31 | 115.17 | | 23.26 | 393.02 | 115.69 | 64.82 |
-| | Diffusers | 19.20 | | | | | | 414.80 | | |
-| | NIM | 9.36 | 4.83 | 4.12 | 83.19 | 29.09 | 19.14 | 316.76 | 94.65 | 55.92 |
-| **B300** | PyTorch | | | | | | | | | |
-| | vLLM-Omni | 14.14 | | 7.19 | 111.42 | | 23.91 | 368.73 | 111.41 | 63.25 |
-| | Diffusers | 54.20 | | | 151.80 | | | 425.00 | | |
-| | NIM | 9.73 | 5.58 | 5.94 | 80.51 | 30.17 | 20.62 | 294.11 | 93.77 | 56.76 |
-
-### Text-to-Image (t2i)
-
-| GPU | Engine | 256p/1 | 256p/4 | 256p/8 | 480p/1 | 480p/4 | 480p/8 | 720p/1 | 720p/4 | 720p/8 |
-|---|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|
-| **RTX PRO 6000 Blackwell** | PyTorch | | | | | | | | 92.61 | 93.11 |
-| | vLLM-Omni | | | | | | | | | |
-| | Diffusers | | | | | | | | | |
-| **H20** | PyTorch | | | | | | | | | 20.92 |
-| | vLLM-Omni | | | | | | | | | |
-| | Diffusers | | | | | | | | | |
-| **H100 NVL** | PyTorch | | 19.73 | 19.86 | | | | | 20.68 | 19.87 |
-| | vLLM-Omni | | | | | | | | | |
-| | Diffusers | | | | | | | | | |
-| **H200 NVL** | PyTorch | | | | | | | | 32.64 | 33.16 |
-| | vLLM-Omni | 2.73 | | 3.20 | 6.28 | | 17.71 | 11.02 | 4.22 | 3.26 |
-| | Diffusers | 5.00 | | | 8.00 | | | 12.00 | | |
-| **H100 80GB HBM3** | PyTorch | | | | | | | | | |
-| | vLLM-Omni | | | | | | | | | |
-| | Diffusers | | | | | | | | | |
-| **H200 141GB HBM3** | PyTorch | | 13.62 | 13.48 | | 13.33 | 13.53 | | 13.78 | 13.50 |
-| | vLLM-Omni | 2.83 | | 4.50 | 5.70 | | 7.16 | 10.24 | 4.23 | 4.43 |
-| | Diffusers | 5.00 | | | 8.00 | | | 11.00 | | |
-| **B200** | PyTorch | | 4.10 | 4.27 | 4.78 | 4.13 | 4.48 | 7.25 | 4.28 | 4.65 |
-| | vLLM-Omni | 2.32 | | 4.58 | 3.29 | | 9.10 | 6.02 | 3.09 | 4.43 |
-| | Diffusers | | | | | | | 8.00 | | |
-| **B300** | PyTorch | | | | | | | | | |
-| | vLLM-Omni | 5.05 | | 7.62 | 3.79 | | 72.65 | 7.08 | 5.79 | 7.24 |
-| | Diffusers | 38.80 | | | 39.40 | | | 40.40 | | |
-
-Notes:
-1. All times measured on identical workloads (same seed, sampler settings, prompt).
-2. 4×/8× GPU configurations use tensor parallelism.
-3. vLLM-Omni numbers are for the upcoming public release in the vLLM-Omni repo; subject to change before GA. Current vLLM-Omni coverage is B200 at 720p.
-4. Diffusers numbers use the HuggingFace `diffusers` integration without custom CUDA graphs; reported at 256p/1, 480p/1, and 720p/1 (single-GPU only).
-5. At 256p, multi-GPU configurations on B300 may underperform single-GPU due to small-workload TP overhead; single-GPU is recommended at this resolution.
-6. PyTorch numbers report average generation (sampling) time from OSS inference benchmarking.
-7. NIM numbers use latency profiles with FP8 precision and report end-to-end `Request Latency s`, including request processing, video generation, output encoding, and returning the response.
-
## Cosmos3-Edge Reasoner
These tables report **Cosmos3-Edge** reasoner serving performance through **vLLM**. Unlike the Generator benchmarks, Reasoner workloads produce autoregressively generated text and measure time to first token (TTFT), end-to-end request latency, request throughput, and output-token throughput. Lower is better for latency metrics; higher is better for throughput.
diff --git a/inference_benchmarks/cosmos3-edge-generator.md b/inference_benchmarks/cosmos3-edge-generator.md
new file mode 100644
index 00000000..9f48aaa2
--- /dev/null
+++ b/inference_benchmarks/cosmos3-edge-generator.md
@@ -0,0 +1,201 @@
+# Cosmos3-Edge Generator Inference Benchmarks
+
+[Back to the inference benchmark index](../inference_benchmarks.md)
+
+These tables report **Cosmos3-Edge** Generator latency in seconds. Lower latency is better, and empty cells indicate that a run has not been completed rather than an unsupported combination.
+
+Cosmos3-Edge supports **256p and 480p**, so 480p is its highest resolution. Every row reports one GPU configuration, named in the **GPUs** column: one GPU where the model fits on a single device at 480p, and eight GPUs where it does not. Cosmos3-Edge fits on a single GPU or one integrated computing platform at 480p, so all populated rows report one. Within a platform's block every engine reports the same configuration, so the rows can be compared directly.
+
+Video benchmarks generate **121 frames**. vLLM-Omni values report end-to-end latency, PyTorch values report average generation latency, and TensorRT-LLM values report average generation latency from PBR `#308000`.
+
+## Table of Contents
+
+- [Text-to-Image (t2i)](#text-to-image-t2i)
+- [Text-to-Video (t2v)](#text-to-video-t2v)
+- [Image-to-Video (i2v)](#image-to-video-i2v)
+- [Video-to-Video (v2v)](#video-to-video-v2v)
+
+## Text-to-Image (t2i)
+
+| GPU or Platform | Engine | GPUs | 256p | 480p |
+|---|---|:-:|---:|---:|
+| **B200 SXM 192 GB** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | 1 | 0.52 | 0.53 |
+| **B300** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | 1 | 0.81 | 0.82 |
+| **H200 SXM 141 GB** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | 1 | 0.58 | 0.58 |
+| **H200 NVL** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **H100 SXM 80 GB** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | 1 | 0.58 | 0.59 |
+| **H100 NVL 96 GB** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **H20 SXM 96 GB** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | 1 | 0.79 | 1.43 |
+| **RTX PRO 6000 Blackwell Server Edition** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | 1 | 0.57 | 0.66 |
+| **DGX Station** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **DGX Spark** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **Jetson AGX Thor T5000, 128 GB, MAXN** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **Jetson T3000, 32 GB, 1100 MHz** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **Jetson T2000, 16 GB, 702 MHz, THOR_NANO** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+
+## Text-to-Video (t2v)
+
+| GPU or Platform | Engine | GPUs | 256p | 480p |
+|---|---|:-:|---:|---:|
+| **B200 SXM 192 GB** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | 1 | 1.05 | 7.84 |
+| **B300** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | 1 | 1.00 | 7.22 |
+| **H200 SXM 141 GB** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | 1 | 1.77 | 14.89 |
+| **H200 NVL** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **H100 SXM 80 GB** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | 1 | 1.83 | 15.09 |
+| **H100 NVL 96 GB** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **H20 SXM 96 GB** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | 1 | 6.91 | 59.19 |
+| **RTX PRO 6000 Blackwell Server Edition** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | 1 | 2.77 | 26.13 |
+| **DGX Station** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **DGX Spark** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **Jetson AGX Thor T5000, 128 GB, MAXN** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **Jetson T3000, 32 GB, 1100 MHz** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **Jetson T2000, 16 GB, 702 MHz, THOR_NANO** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+
+## Image-to-Video (i2v)
+
+| GPU or Platform | Engine | GPUs | 256p | 480p |
+|---|---|:-:|---:|---:|
+| **B200 SXM 192 GB** | PyTorch | 1 | | 7.45 |
+| | vLLM-Omni | 1 | | 7.09 |
+| | TensorRT-LLM | 1 | 1.23 | 8.55 |
+| **B300** | PyTorch | 1 | | 6.84 |
+| | vLLM-Omni | 1 | | 8.74 |
+| | TensorRT-LLM | 1 | 1.42 | 8.04 |
+| **H200 SXM 141 GB** | PyTorch | 1 | | 12.31 |
+| | vLLM-Omni | 1 | | 13.13 |
+| | TensorRT-LLM | 1 | 1.99 | 15.89 |
+| **H200 NVL** | PyTorch | 1 | | 14.07 |
+| | vLLM-Omni | 1 | | 14.15 |
+| | TensorRT-LLM | — | | |
+| **H100 SXM 80 GB** | PyTorch | 1 | | 12.68 |
+| | vLLM-Omni | 1 | | 13.33 |
+| | TensorRT-LLM | 1 | 2.08 | 15.95 |
+| **H100 NVL 96 GB** | PyTorch | 1 | | 16.42 |
+| | vLLM-Omni | 1 | | 17.33 |
+| | TensorRT-LLM | — | | |
+| **H20 SXM 96 GB** | PyTorch | 1 | | 52.83 |
+| | vLLM-Omni | 1 | | 53.94 |
+| | TensorRT-LLM | 1 | 7.50 | 62.08 |
+| **RTX PRO 6000 Blackwell Server Edition** | PyTorch | 1 | | 21.92 |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | 1 | 3.09 | 27.55 |
+| **DGX Station** | PyTorch | 1 | | 6.31 |
+| | vLLM-Omni | 1 | | 7.13 |
+| | TensorRT-LLM | — | | |
+| **DGX Spark** | PyTorch | 1 | | 103.36 |
+| | vLLM-Omni | 1 | | 89.41 |
+| | TensorRT-LLM | — | | |
+| **Jetson AGX Thor T5000, 128 GB, MAXN** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **Jetson T3000, 32 GB, 1100 MHz** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **Jetson T2000, 16 GB, 702 MHz, THOR_NANO** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+
+## Video-to-Video (v2v)
+
+| GPU or Platform | Engine | GPUs | 256p | 480p |
+|---|---|:-:|---:|---:|
+| **B200 SXM 192 GB** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | 1 | 1.15 | 7.94 |
+| **B300** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | 1 | 1.24 | 7.35 |
+| **H200 SXM 141 GB** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | 1 | 1.91 | 15.09 |
+| **H200 NVL** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **H100 SXM 80 GB** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | 1 | 1.95 | 15.28 |
+| **H100 NVL 96 GB** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **H20 SXM 96 GB** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | 1 | 7.04 | 60.03 |
+| **RTX PRO 6000 Blackwell Server Edition** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | 1 | 2.86 | 26.21 |
+| **DGX Station** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **DGX Spark** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **Jetson AGX Thor T5000, 128 GB, MAXN** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **Jetson T3000, 32 GB, 1100 MHz** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+| **Jetson T2000, 16 GB, 702 MHz, THOR_NANO** | PyTorch | — | | |
+| | vLLM-Omni | — | | |
+| | TensorRT-LLM | — | | |
+
+Notes:
+1. The **GPUs** column gives the number of GPUs behind every value in that row. All current measurements use one GPU or one integrated computing platform.
+2. Values are average end-to-end or generation latency in seconds; lower is better.
+3. TensorRT-LLM values come from PBR `#308000`, which covers the six datacenter GPUs only; the DGX and Jetson platforms were not part of that campaign.
+4. vLLM-Omni and PyTorch were measured for i2v only, so their rows are empty in the other three sections.
+5. Video measurements generate **121 output frames**.
+6. PyTorch values report average generation latency rather than diffusion-only latency.
+7. Diffusers and NIM have no Cosmos3-Edge coverage yet, so they are not listed.
diff --git a/inference_benchmarks/cosmos3-nano-fp8-generator.md b/inference_benchmarks/cosmos3-nano-fp8-generator.md
new file mode 100644
index 00000000..9690dc1f
--- /dev/null
+++ b/inference_benchmarks/cosmos3-nano-fp8-generator.md
@@ -0,0 +1,433 @@
+# Cosmos3-Nano-FP8 Generator Inference Benchmarks
+
+[Back to the inference benchmark index](../inference_benchmarks.md)
+
+These tables report **Cosmos3-Nano-FP8** Generator latency in seconds, for the FP8 quantized Cosmos3-Nano checkpoint. Lower is better. The BF16 numbers for the same model are on the [Cosmos3-Nano page](cosmos3-nano-generator.md).
+
+Every row reports one GPU configuration, named in the **GPUs** column, and all three resolutions in that row come from it. The configuration is one GPU when the model fits on a single device at its highest resolution, 720p, and eight GPUs when it does not. Within one GPU's block every engine reports the same configuration, so a column can be read straight across the runtimes. All populated rows report one GPU.
+
+Empty cells mean that a run has not been completed for that GPU, engine, or resolution; they do not indicate that a combination is unsupported.
+
+## Table of Contents
+
+- [Benchmark methodology](#benchmark-methodology)
+- [Workload definitions](#workload-definitions)
+- [Primary vision generation](#primary-vision-generation)
+ - [Text-to-Video (t2v)](#text-to-video-t2v)
+ - [Image-to-Video (i2v)](#image-to-video-i2v)
+ - [Text-to-Image (t2i)](#text-to-image-t2i)
+- [Additional audiovisual generation](#additional-audiovisual-generation)
+ - [Video-to-Video (v2v)](#video-to-video-v2v)
+ - [Text-to-Audio-and-Video (t2av)](#text-to-audio-and-video-t2av)
+ - [Video-to-Audio-and-Video (v2av)](#video-to-audio-and-video-v2av)
+ - [Image-to-Audio-and-Video (i2av)](#image-to-audio-and-video-i2av)
+- [Transfer generation](#transfer-generation)
+- [Action generation](#action-generation)
+ - [Forward Dynamics — Autonomous Vehicle (AV)](#forward-dynamics--autonomous-vehicle-av)
+ - [Forward Dynamics — Camera](#forward-dynamics--camera)
+ - [Forward Dynamics — Robot](#forward-dynamics--robot)
+ - [Inverse Dynamics — Autonomous Vehicle (AV)](#inverse-dynamics--autonomous-vehicle-av)
+ - [Inverse Dynamics — Robot](#inverse-dynamics--robot)
+ - [Policy — Autonomous Vehicle (AV)](#policy--autonomous-vehicle-av)
+ - [Policy — Robot](#policy--robot)
+
+## Benchmark methodology
+
+PyTorch values are from PBR `#309161`, **FP8 Cosmos3-Nano/Super (regular non-distilled) Generator PyTorch Inference Benchmarking**, reporting average generation latency over datacenter configurations at 1, 4, and 8 GPUs. Diffusers values are from PBR `#309434`, **FP8 Cosmos3-Nano/Super Generator Diffusers Inference Benchmarking**, measured on a single GPU only and at 480p and 720p only, which is why the 256p column is empty for Diffusers and why its rows are empty wherever a block reports eight GPUs. Neither campaign covered H100 NVL or H200 NVL, so those GPUs are absent from this page. GB300 appears only in the Diffusers campaign. vLLM-Omni, TensorRT-LLM, and NIM have no FP8 results yet. Values are rounded to two decimal places.
+
+These reports establish the reported timing matrix but do not expose every prompt and action payload in this repository. The linked public recipes explain modality behavior and provide representative payloads; their example-specific frame counts and action chunk sizes should not be treated as the exact internal benchmark inputs.
+
+## Workload definitions
+
+| Workload | Input | Output |
+|---|---|---|
+| Text-to-image (`t2i`) | Text prompt | Generated image |
+| Text-to-video (`t2v`) | Text prompt | Generated video |
+| Image-to-video (`i2v`) | Text prompt and source image | Generated video |
+| Video-to-video (`v2v`) | Text prompt and source video | Generated video |
+| Text-to-audio-and-video (`t2av`) | Text prompt | Synchronized video and sound |
+| Video-to-audio-and-video (`v2av`) | Text prompt and source video | Generated video with synchronized sound |
+| Image-to-audio-and-video (`i2av`) | Text prompt and source image | Generated video with synchronized sound |
+| Transfer video-to-video (`transfer`) | Text prompt, source video, and one control hint | Generated video steered by that hint |
+| Forward dynamics | Initial visual observation and an action trajectory | Future-observation rollout video |
+| Inverse dynamics | Observed video | Recovered action trajectory; some serving integrations also return video |
+| Policy | Initial visual observation, instruction, and optional state | Predicted action trajectory and, for general Generator paths, a rollout video |
+
+The PBR uses `t2av`, `v2av`, and `i2av`; some public recipes call the same sound-producing modes `t2vs`, `v2vs`, and `i2vs`. See the [audiovisual cookbook](../cookbooks/cosmos3/generator/audiovisual/README.md) for generation inputs and the [action cookbook](../cookbooks/cosmos3/generator/action/README.md) for action representations and output contracts.
+
+## Primary vision generation
+
+### Text-to-Video (t2v)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 4.71 | 47.34 | 173.02 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 11.82 | 112.34 | 427.62 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 3.12 | 26.01 | 94.01 |
+| | Diffusers | 1 | | 69.55 | 237.29 |
+| **H200 141GB HBM3** | PyTorch | 1 | 3.09 | 26.59 | 94.57 |
+| | Diffusers | 1 | | 68.32 | 237.18 |
+| **B200** | PyTorch | 1 | 1.97 | 14.85 | 51.85 |
+| | Diffusers | 1 | | 39.70 | 124.10 |
+| **B300** | PyTorch | 1 | 1.99 | 13.68 | 46.41 |
+| | Diffusers | 1 | | 37.61 | 115.14 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 34.53 | 97.30 |
+
+### Image-to-Video (i2v)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 4.50 | 45.96 | 169.15 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 11.19 | 110.19 | 419.99 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 2.96 | 25.04 | 91.65 |
+| | Diffusers | 1 | | 71.06 | 241.53 |
+| **H200 141GB HBM3** | PyTorch | 1 | 2.94 | 25.56 | 92.44 |
+| | Diffusers | 1 | | 69.69 | 237.95 |
+| **B200** | PyTorch | 1 | 1.87 | 14.24 | 50.24 |
+| | Diffusers | 1 | | 40.69 | 126.07 |
+| **B300** | PyTorch | 1 | 1.78 | 13.08 | 44.94 |
+| | Diffusers | 1 | | 38.35 | 117.18 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 34.96 | 99.37 |
+
+### Text-to-Image (t2i)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 0.97 | 1.02 | 1.50 |
+| | Diffusers | 1 | | 7.29 | |
+| **H20** | PyTorch | 1 | 1.27 | 1.74 | 3.25 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 1.16 | 1.14 | 1.21 |
+| | Diffusers | 1 | | 7.50 | 7.68 |
+| **H200 141GB HBM3** | PyTorch | 1 | 1.12 | 1.14 | 1.21 |
+| | Diffusers | 1 | | 7.44 | 7.74 |
+| **B200** | PyTorch | 1 | 0.96 | 0.92 | 0.97 |
+| | Diffusers | 1 | | 6.82 | 6.94 |
+| **B300** | PyTorch | 1 | 0.95 | 0.95 | 1.51 |
+| | Diffusers | 1 | | 10.28 | 6.71 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 11.79 | 13.19 |
+
+Notes:
+1. All times measured on identical workloads (same seed, sampler settings, prompt).
+2. Multi-GPU configurations use tensor parallelism.
+3. Values are average generation latency in seconds; lower is better.
+4. The **GPUs** column gives the number of GPUs behind every value in that row, and is the same for every engine in a GPU block so the rows can be compared directly.
+5. Diffusers FP8 was measured on one GPU at 480p and 720p only.
+6. FP8 is faster than BF16 for the PyTorch path throughout. For the Diffusers path it only pays off on long video workloads: short ones are slower in FP8, `t2i` consistently so by roughly a factor of two, which suggests a fixed quantization overhead that the short runs cannot amortize. Compare against the BF16 page before choosing a precision for a short workload.
+
+## Additional audiovisual generation
+
+### Video-to-Video (v2v)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 4.40 | 47.39 | 175.87 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 10.99 | 112.59 | 437.65 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 2.93 | 25.89 | 95.20 |
+| | Diffusers | 1 | | 72.01 | 241.38 |
+| **H200 141GB HBM3** | PyTorch | 1 | 2.90 | 26.51 | 96.80 |
+| | Diffusers | 1 | | 70.17 | 239.24 |
+| **B200** | PyTorch | 1 | 1.85 | 14.69 | 52.19 |
+| | Diffusers | 1 | | 41.72 | 127.42 |
+| **B300** | PyTorch | 1 | 1.92 | 13.61 | 47.32 |
+| | Diffusers | 1 | | 39.99 | 118.73 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 35.97 | 100.27 |
+
+### Text-to-Audio-and-Video (t2av)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 7.67 | 50.58 | 178.94 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 17.97 | 120.72 | 442.78 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 4.88 | 28.50 | 97.19 |
+| | Diffusers | 1 | | 70.46 | 239.14 |
+| **H200 141GB HBM3** | PyTorch | 1 | 4.79 | 28.21 | 99.38 |
+| | Diffusers | 1 | | 68.99 | 237.11 |
+| **B200** | PyTorch | 1 | 3.10 | 16.48 | 54.04 |
+| | Diffusers | 1 | | 40.71 | 124.89 |
+| **B300** | PyTorch | 1 | 3.12 | 15.17 | 49.50 |
+| | Diffusers | 1 | | 38.13 | 116.44 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 34.89 | 100.22 |
+
+### Video-to-Audio-and-Video (v2av)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | — | | | |
+| | Diffusers | — | | | |
+| **H20** | PyTorch | — | | | |
+| | Diffusers | — | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 73.07 | 243.26 |
+| **H200 141GB HBM3** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 71.80 | 241.17 |
+| **B200** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 42.28 | 126.29 |
+| **B300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 39.94 | 120.27 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 36.41 | 101.35 |
+
+### Image-to-Audio-and-Video (i2av)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 7.30 | 48.80 | 174.71 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 17.08 | 115.28 | 428.45 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 4.63 | 27.33 | 94.44 |
+| | Diffusers | 1 | | 72.07 | 243.07 |
+| **H200 141GB HBM3** | PyTorch | 1 | 4.54 | 27.44 | 97.66 |
+| | Diffusers | 1 | | 70.18 | 241.70 |
+| **B200** | PyTorch | 1 | 2.96 | 15.67 | 52.20 |
+| | Diffusers | 1 | | 41.66 | 126.91 |
+| **B300** | PyTorch | 1 | 2.81 | 14.60 | 47.27 |
+| | Diffusers | 1 | | 39.34 | |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 36.51 | 101.85 |
+
+## Transfer generation
+
+Transfer conditions a video-to-video generation on a structural control hint
+extracted from the source video. Each control is reported separately because
+the hint changes how much of the frame the model must synthesise.
+
+| GPU | Transfer control | Engine | GPUs | 256p | 480p | 720p |
+|---|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | blur | PyTorch | 1 | 15.92 | 99.23 | 369.40 |
+| | | Diffusers | 1 | | | |
+| | depth | PyTorch | 1 | 15.34 | 102.88 | 379.90 |
+| | | Diffusers | 1 | | | |
+| | edge | PyTorch | 1 | 13.27 | 99.61 | 374.57 |
+| | | Diffusers | 1 | | | |
+| | multi_control | PyTorch | — | | | |
+| | | Diffusers | — | | | |
+| | seg | PyTorch | 1 | 14.54 | 104.96 | 378.47 |
+| | | Diffusers | 1 | | | |
+| | wsm | PyTorch | 1 | 12.81 | 78.87 | 280.91 |
+| | | Diffusers | 1 | | | 430.19 |
+| **H20** | blur | PyTorch | 1 | 36.48 | 238.41 | 918.21 |
+| | | Diffusers | 1 | | | |
+| | depth | PyTorch | 1 | 34.13 | 243.68 | 951.21 |
+| | | Diffusers | 1 | | | |
+| | edge | PyTorch | 1 | 29.64 | 238.38 | 947.97 |
+| | | Diffusers | 1 | | | |
+| | multi_control | PyTorch | 1 | 36.57 | 385.10 | 1678.80 |
+| | | Diffusers | 1 | | | |
+| | seg | PyTorch | 1 | 31.20 | 239.56 | 992.60 |
+| | | Diffusers | 1 | | | |
+| | wsm | PyTorch | 1 | 28.15 | 186.34 | 707.32 |
+| | | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | blur | PyTorch | 1 | 10.37 | 55.94 | 198.76 |
+| | | Diffusers | 1 | | 171.90 | 600.30 |
+| | depth | PyTorch | 1 | 9.83 | 57.44 | 207.16 |
+| | | Diffusers | 1 | | 178.89 | 606.60 |
+| | edge | PyTorch | 1 | 8.49 | 55.27 | 204.24 |
+| | | Diffusers | 1 | | 172.75 | 597.01 |
+| | multi_control | PyTorch | 1 | 10.51 | 91.48 | 367.08 |
+| | | Diffusers | 1 | | | |
+| | seg | PyTorch | 1 | 10.03 | 56.62 | 214.56 |
+| | | Diffusers | 1 | | 174.09 | 601.13 |
+| | wsm | PyTorch | 1 | 8.33 | 44.52 | 153.26 |
+| | | Diffusers | 1 | | 84.48 | 264.67 |
+| **H200 141GB HBM3** | blur | PyTorch | 1 | 10.32 | 55.96 | 205.31 |
+| | | Diffusers | 1 | | 169.37 | 598.78 |
+| | depth | PyTorch | 1 | 9.70 | 58.92 | 211.20 |
+| | | Diffusers | 1 | | 177.22 | 603.37 |
+| | edge | PyTorch | 1 | 8.60 | 56.78 | 208.28 |
+| | | Diffusers | 1 | | 169.21 | 594.04 |
+| | multi_control | PyTorch | 1 | 10.46 | 92.81 | 382.20 |
+| | | Diffusers | 1 | | | |
+| | seg | PyTorch | 1 | 9.68 | 58.18 | 209.54 |
+| | | Diffusers | 1 | | 170.62 | 601.64 |
+| | wsm | PyTorch | 1 | 8.39 | 45.06 | 154.98 |
+| | | Diffusers | 1 | | 82.92 | 263.74 |
+| **B200** | blur | PyTorch | 1 | 7.02 | 32.23 | 110.23 |
+| | | Diffusers | 1 | | 94.88 | 298.51 |
+| | depth | PyTorch | 1 | 6.68 | 33.48 | 113.49 |
+| | | Diffusers | 1 | | 98.03 | 307.64 |
+| | edge | PyTorch | 1 | 5.79 | 31.53 | 111.67 |
+| | | Diffusers | 1 | | 96.11 | 302.90 |
+| | multi_control | PyTorch | — | | | |
+| | | Diffusers | — | | | |
+| | seg | PyTorch | 1 | 6.65 | 33.21 | 114.39 |
+| | | Diffusers | 1 | | 97.13 | 301.15 |
+| | wsm | PyTorch | 1 | 5.78 | 26.19 | 85.06 |
+| | | Diffusers | 1 | | 48.75 | 138.10 |
+| **B300** | blur | PyTorch | 1 | 8.30 | 31.29 | 101.38 |
+| | | Diffusers | 1 | | | 278.49 |
+| | depth | PyTorch | 1 | 7.81 | 32.60 | 105.09 |
+| | | Diffusers | 1 | | 93.48 | 282.93 |
+| | edge | PyTorch | 1 | 6.08 | 31.68 | 103.18 |
+| | | Diffusers | 1 | | 89.60 | 277.25 |
+| | multi_control | PyTorch | — | | | |
+| | | Diffusers | — | | | |
+| | seg | PyTorch | 1 | 7.14 | 32.89 | 106.26 |
+| | | Diffusers | 1 | | 89.99 | 280.71 |
+| | wsm | PyTorch | 1 | 5.89 | 25.42 | 78.99 |
+| | | Diffusers | 1 | | 46.64 | 129.77 |
+| **GB300** | blur | PyTorch | 1 | | | |
+| | | Diffusers | 1 | | 80.61 | 236.36 |
+| | depth | PyTorch | 1 | | | |
+| | | Diffusers | 1 | | 81.57 | 238.78 |
+| | edge | PyTorch | 1 | | | |
+| | | Diffusers | 1 | | 80.54 | 235.31 |
+| | multi_control | PyTorch | — | | | |
+| | | Diffusers | — | | | |
+| | seg | PyTorch | 1 | | | |
+| | | Diffusers | 1 | | 81.67 | 237.79 |
+| | wsm | PyTorch | 1 | | | |
+| | | Diffusers | 1 | | 42.26 | 110.70 |
+
+Transfer notes:
+1. Control hints follow the `extra_params` names: `blur`, `depth`, `edge`, `multi_control`, `seg`, and `wsm`. `multi_control` combines several hints in one request.
+2. The PyTorch campaign reports `segmentation`, which is the same control as `seg` in the Diffusers campaign.
+3. Diffusers FP8 has no `multi_control` measurements.
+
+## Action generation
+
+### Forward Dynamics — Autonomous Vehicle (AV)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 5.80 | 5.78 | 5.80 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 13.44 | 13.32 | 13.44 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 3.54 | 3.53 | 3.53 |
+| | Diffusers | 1 | | 11.68 | 12.20 |
+| **H200 141GB HBM3** | PyTorch | 1 | 3.45 | 3.47 | 3.46 |
+| | Diffusers | 1 | | 11.19 | 11.73 |
+| **B200** | PyTorch | 1 | 2.16 | 2.16 | 2.16 |
+| | Diffusers | 1 | | 8.05 | 8.42 |
+| **B300** | PyTorch | 1 | 2.11 | 2.09 | 2.10 |
+| | Diffusers | 1 | | 8.83 | 8.96 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 7.71 | 7.64 |
+
+### Forward Dynamics — Camera
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 5.47 | 5.49 | 5.48 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 12.69 | 12.57 | 12.58 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 3.38 | 3.37 | 3.36 |
+| | Diffusers | 1 | | | |
+| **H200 141GB HBM3** | PyTorch | 1 | 3.29 | 3.30 | 3.29 |
+| | Diffusers | 1 | | | |
+| **B200** | PyTorch | 1 | 2.06 | 2.06 | 2.06 |
+| | Diffusers | 1 | | | |
+| **B300** | PyTorch | 1 | 1.98 | 1.98 | 2.06 |
+| | Diffusers | 1 | | | |
+
+### Forward Dynamics — Robot
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 1.28 | 1.28 | 1.28 |
+| | Diffusers | 1 | | | 5.63 |
+| **H20** | PyTorch | 1 | 2.85 | 2.84 | 2.84 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 0.85 | 0.85 | 0.85 |
+| | Diffusers | 1 | | 4.63 | 4.79 |
+| **H200 141GB HBM3** | PyTorch | 1 | 0.84 | 0.84 | 0.84 |
+| | Diffusers | 1 | | 4.58 | 4.69 |
+| **B200** | PyTorch | 1 | 0.61 | 0.61 | 0.60 |
+| | Diffusers | 1 | | 4.09 | 4.35 |
+| **B300** | PyTorch | 1 | 0.87 | 0.88 | 0.60 |
+| | Diffusers | 1 | | 3.78 | 5.98 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 5.70 | 6.32 |
+
+### Inverse Dynamics — Autonomous Vehicle (AV)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 9.02 | 9.01 | 9.00 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 21.15 | 21.36 | 21.15 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 5.45 | 5.44 | 5.44 |
+| | Diffusers | 1 | | 11.61 | 12.21 |
+| **H200 141GB HBM3** | PyTorch | 1 | 5.32 | 5.39 | 5.32 |
+| | Diffusers | 1 | | 11.10 | 11.65 |
+| **B200** | PyTorch | 1 | 3.25 | 3.24 | 3.24 |
+| | Diffusers | 1 | | 8.00 | 8.27 |
+| **B300** | PyTorch | 1 | 3.15 | 3.14 | 3.13 |
+| | Diffusers | 1 | | 8.90 | 8.95 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 7.85 | 7.88 |
+
+### Inverse Dynamics — Robot
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 1.86 | 1.85 | 1.85 |
+| | Diffusers | 1 | | | 5.65 |
+| **H20** | PyTorch | 1 | 4.32 | 4.28 | 4.31 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 1.21 | 1.22 | 1.22 |
+| | Diffusers | 1 | | 4.75 | 4.79 |
+| **H200 141GB HBM3** | PyTorch | 1 | 1.19 | 1.19 | 1.19 |
+| | Diffusers | 1 | | 4.64 | 4.72 |
+| **B200** | PyTorch | 1 | 0.84 | 0.86 | 0.84 |
+| | Diffusers | 1 | | 4.02 | 4.18 |
+| **B300** | PyTorch | 1 | 0.87 | 0.84 | 0.84 |
+| | Diffusers | 1 | | | 6.03 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 6.57 | 6.08 |
+
+### Policy — Autonomous Vehicle (AV)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 5.80 | 5.79 | 5.80 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 13.44 | 13.44 | 13.44 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 3.54 | 3.54 | 3.54 |
+| | Diffusers | 1 | | | |
+| **H200 141GB HBM3** | PyTorch | 1 | 3.51 | 3.49 | 3.51 |
+| | Diffusers | 1 | | | |
+| **B200** | PyTorch | 1 | 2.17 | 2.17 | 2.14 |
+| | Diffusers | 1 | | | |
+| **B300** | PyTorch | 1 | 2.14 | 2.13 | 2.16 |
+| | Diffusers | 1 | | | |
+
+### Policy — Robot
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 1.28 | 1.29 | 1.24 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 2.75 | 2.87 | 2.75 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 0.84 | 0.84 | 0.85 |
+| | Diffusers | 1 | | | |
+| **H200 141GB HBM3** | PyTorch | 1 | 0.83 | 0.82 | 0.85 |
+| | Diffusers | 1 | | | |
+| **B200** | PyTorch | 1 | 0.60 | 0.61 | 0.62 |
+| | Diffusers | 1 | | | |
+| **B300** | PyTorch | 1 | 0.89 | 0.85 | 0.86 |
+| | Diffusers | 1 | | | |
+
+Action and additional-modality notes:
+1. Forward-dynamics cells for the AV domain are the mean of the forward, left, and right trajectories; inverse-dynamics cells are the mean of the two inverse trajectories.
+2. The Diffusers FP8 campaign covers forward and inverse dynamics for the AV and Robot domains only, so the Camera and Policy rows carry PyTorch values alone.
+3. Policy-DROID is a separate checkpoint and was not part of either FP8 campaign.
diff --git a/inference_benchmarks/cosmos3-nano-generator.md b/inference_benchmarks/cosmos3-nano-generator.md
new file mode 100644
index 00000000..f508f38b
--- /dev/null
+++ b/inference_benchmarks/cosmos3-nano-generator.md
@@ -0,0 +1,920 @@
+# Cosmos3-Nano Generator Inference Benchmarks
+
+[Back to the inference benchmark index](../inference_benchmarks.md)
+
+These tables report **Cosmos3-Nano Generator** latency in seconds. Lower is better.
+
+Every row reports one GPU configuration, named in the **GPUs** column, and all three resolutions in that row come from it. The configuration is one GPU when the model fits on a single device at its highest resolution, 720p, and eight GPUs when it does not. Within one GPU's block every engine reports the same configuration, so a column can be read straight across the runtimes. Cosmos3-Nano fits on a single GPU at 720p, so all populated rows here report one GPU.
+
+Empty cells mean that a run has not been completed for that GPU, engine, or resolution; they do not indicate that a combination is unsupported.
+
+## Table of Contents
+
+- [Benchmark methodology](#benchmark-methodology)
+- [Workload definitions](#workload-definitions)
+- [Primary vision generation](#primary-vision-generation)
+ - [Text-to-Video (t2v)](#text-to-video-t2v)
+ - [Image-to-Video (i2v)](#image-to-video-i2v)
+ - [Text-to-Image (t2i)](#text-to-image-t2i)
+- [Additional audiovisual generation](#additional-audiovisual-generation)
+ - [Video-to-Video (v2v)](#video-to-video-v2v)
+ - [Text-to-Audio-and-Video (t2av)](#text-to-audio-and-video-t2av)
+ - [Video-to-Audio-and-Video (v2av)](#video-to-audio-and-video-v2av)
+ - [Image-to-Audio-and-Video (i2av)](#image-to-audio-and-video-i2av)
+- [Transfer generation](#transfer-generation)
+- [Action generation](#action-generation)
+ - [Forward Dynamics — AV](#forward-dynamics--autonomous-vehicle-av)
+ - [Forward Dynamics — Camera](#forward-dynamics--camera)
+ - [Forward Dynamics — Robot](#forward-dynamics--robot)
+ - [Inverse Dynamics — AV](#inverse-dynamics--autonomous-vehicle-av)
+ - [Inverse Dynamics — Robot](#inverse-dynamics--robot)
+ - [Policy — AV](#policy--autonomous-vehicle-av)
+ - [Policy — Robot](#policy--robot)
+ - [Policy — DROID](#policy--droid)
+
+## Benchmark methodology
+
+The primary t2v, i2v, and t2i tables cover PyTorch, vLLM-Omni, Diffusers, TensorRT-LLM, and NIM. Their vLLM-Omni values are from PBR `#307999`, **Cosmos3-Generator vLLM-Omni Inference Benchmarking (t2i, t2v, i2v)**; the PyTorch and NIM values preserve the previously published campaigns. Those tables use BF16 precision, batch size 1, and matched prompts, seeds, and sampler settings where documented. Video workloads follow the standard Cosmos3 generation profile of 189 frames at 24 FPS unless a resolution tier limits frame count.
+
+The additional audiovisual and action tables come from three internal benchmark reports. PyTorch values are from PBR `#308197`, **Cosmos3-Generator OSS Inference Benchmarking 32B and 8B (189 frames)**: average generation (sampling) latency from the native OSS path, using **CUDA Graphs disabled** and the **latency** automatic-sharding preset. vLLM-Omni values for text-to-audio-and-video (`t2av`/`t2vs`) and image-to-audio-and-video (`i2av`/`i2vs`) are from PBR `#308195`. vLLM-Omni action values are from PBR `#308481`, **Cosmos3-Generator vLLM-Omni Inference Benchmarking (action)**, measured with the `vllm/vllm-omni:cosmos3` image and the official action cookbook samples; `DIFFUSION_ATTENTION_BACKEND=TORCH_SDPA` was not set. Forward-dynamics cells are the mean of `av_forward`, `av_left`, and `av_right`; inverse-dynamics cells are the mean of `av_inverse_0` and `av_inverse_1`. That action sweep covers 1, 2, and 4 GPUs only, because its 8-GPU Ulysses runs failed a sequence-length divisibility check; those rows therefore report the single-GPU configuration. Policy-DROID is a separate checkpoint and was measured only at 480p on one GPU. That action sweep did not cover Super on H20, H100 NVL, or H100 80GB HBM3. Diffusers values come from four further reports: PBR `#308202` (all modalities) and PBR `#308451` (video-to-video) on one GPU, PBR `#308918` for 4- and 8-GPU runs, and PBR `#308587` for transfer. vLLM-Omni transfer values are from PBR `#308574`. Where PBR `#308918` offers several tensor- and context-parallel splits at the same GPU count, the fastest is published. Its 1-GPU numbers are not used, because that sweep ran a different denoising-step budget than the single-GPU reports. TensorRT-LLM values are from PBR `#308000`, **Cosmos3-Generator TRT-LLM Inference Benchmarking**, which sweeps tensor-parallel, CFG-parallel, and Ulysses-parallel splits at each GPU count; the fastest split at the count a row reports is the one published. That campaign covers six GPUs, so the TensorRT-LLM rows for H100 NVL and H200 NVL are empty, and it includes no action workloads. Values are rounded to two decimal places.
+
+These reports establish the reported timing matrix but do not expose every prompt and action payload in this repository. The linked public recipes explain modality behavior and provide representative payloads; their example-specific frame counts and action chunk sizes should not be treated as the exact internal benchmark inputs.
+
+## Workload definitions
+
+| Workload | Input | Output |
+|---|---|---|
+| Video-to-video (`v2v`) | Text prompt and source video | Generated video |
+| Text-to-audio-and-video (`t2av`) | Text prompt | Synchronized video and sound |
+| Video-to-audio-and-video (`v2av`) | Text prompt and source video | Generated video with synchronized sound |
+| Image-to-audio-and-video (`i2av`) | Text prompt and source image | Generated video with synchronized sound |
+| Transfer video-to-video (`transfer`) | Text prompt, source video, and one control hint | Generated video steered by that hint |
+| Forward dynamics | Initial visual observation and an action trajectory | Future-observation rollout video |
+| Inverse dynamics | Observed video | Recovered action trajectory; some serving integrations also return video |
+| Policy | Initial visual observation, instruction, and optional state | Predicted action trajectory and, for general Generator paths, a rollout video |
+| Policy-DROID | Multiview wrist/exterior observations for the DROID embodiment | Predicted action chunk from the Policy-DROID checkpoint |
+
+The PBR uses `t2av`, `v2av`, and `i2av`; some public recipes call the same sound-producing modes `t2vs`, `v2vs`, and `i2vs`. See the [audiovisual cookbook](../cookbooks/cosmos3/generator/audiovisual/README.md) for generation inputs and the [action cookbook](../cookbooks/cosmos3/generator/action/README.md) for action representations and output contracts. vLLM-Omni request shapes are maintained in the [Nano recipe](https://github.com/vllm-project/vllm-omni/blob/main/recipes/cosmos3/Cosmos3-Nano.md). Public recipes cover more embodiments than this PBR; the action tables below intentionally use only its measured domain rows.
+
+## Primary vision generation
+
+### Text-to-Video (t2v)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 13.95 | 180.81 | 786.37 |
+| | vLLM-Omni | 1 | 10.65 | 105.61 | 371.53 |
+| | Diffusers | 1 | 11.20 | 112.00 | 392.00 |
+| | TensorRT-LLM | 1 | 10.27 | 102.55 | 369.78 |
+| | NIM | 1 | 7.93 | 82.69 | 318.69 |
+| **H20** | PyTorch | 1 | 30.57 | 257.51 | 931.39 |
+| | vLLM-Omni | 1 | 28.58 | 256.97 | 929.81 |
+| | Diffusers | 1 | 30.20 | 258.00 | 926.00 |
+| | TensorRT-LLM | 1 | 26.92 | 251.79 | 908.90 |
+| | NIM | 1 | 17.81 | 192.07 | 771.37 |
+| **H100 NVL** | PyTorch | 1 | 10.03 | 84.12 | 297.27 |
+| | vLLM-Omni | 1 | 9.25 | 80.75 | 281.99 |
+| | Diffusers | 1 | 11.00 | 90.00 | 324.20 |
+| | TensorRT-LLM | — | | | |
+| | NIM | 1 | 7.09 | 68.01 | 267.73 |
+| **H200 NVL** | PyTorch | 1 | 8.17 | 69.79 | 244.39 |
+| | vLLM-Omni | 1 | 7.44 | 64.58 | 240.05 |
+| | Diffusers | 1 | 9.00 | 74.00 | 276.20 |
+| | TensorRT-LLM | — | | | |
+| | NIM | 1 | 5.87 | 57.10 | 229.63 |
+| **H100 80GB HBM3** | PyTorch | 1 | 7.61 | 59.83 | 207.78 |
+| | vLLM-Omni | 1 | 6.97 | 58.17 | 202.29 |
+| | Diffusers | 1 | 9.00 | 68.00 | 240.00 |
+| | TensorRT-LLM | 1 | 6.50 | 60.10 | 223.51 |
+| | NIM | 1 | 5.72 | 51.73 | 199.46 |
+| **H200 141GB HBM3** | PyTorch | 1 | 7.53 | 60.18 | 214.28 |
+| | vLLM-Omni | 1 | 6.79 | 58.14 | 208.36 |
+| | Diffusers | 1 | 9.00 | 67.00 | 239.60 |
+| | TensorRT-LLM | 1 | 6.42 | 60.57 | 225.06 |
+| | NIM | 1 | 5.72 | 51.90 | 200.63 |
+| **B200** | PyTorch | 1 | 4.56 | 33.20 | 114.85 |
+| | vLLM-Omni | 1 | 4.03 | 32.04 | 107.79 |
+| | Diffusers | 1 | 7.00 | 36.80 | 117.00 |
+| | TensorRT-LLM | 1 | 3.43 | 28.28 | 100.02 |
+| | NIM | 1 | 3.72 | 26.68 | 93.33 |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | 4.46 | 32.18 | 102.10 |
+| | Diffusers | 1 | 6.40 | 39.32 | 121.74 |
+| | TensorRT-LLM | 1 | 3.31 | 26.52 | 91.15 |
+| | NIM | 1 | 4.51 | 27.49 | 90.39 |
+
+### Image-to-Video (i2v)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 14.08 | 182.14 | 788.80 |
+| | vLLM-Omni | 1 | 11.04 | 107.77 | 376.44 |
+| | Diffusers | 1 | 12.00 | 112.00 | 397.00 |
+| | TensorRT-LLM | 1 | 10.77 | 105.03 | 374.89 |
+| | NIM | 1 | 8.23 | 84.58 | 326.96 |
+| **H20** | PyTorch | 1 | 31.36 | 257.10 | 933.07 |
+| | vLLM-Omni | 1 | 29.50 | 261.56 | 940.16 |
+| | Diffusers | 1 | 31.00 | 258.00 | 925.00 |
+| | TensorRT-LLM | 1 | 28.07 | 254.79 | 915.71 |
+| | NIM | 1 | 18.67 | 195.10 | 774.88 |
+| **H100 NVL** | PyTorch | 1 | 10.19 | 84.50 | 298.57 |
+| | vLLM-Omni | 1 | 9.62 | 82.61 | 286.19 |
+| | Diffusers | 1 | 11.00 | 91.00 | 325.20 |
+| | TensorRT-LLM | — | | | |
+| | NIM | 1 | 7.39 | 69.39 | 272.29 |
+| **H200 NVL** | PyTorch | 1 | 8.27 | 69.99 | 246.62 |
+| | vLLM-Omni | 1 | 7.83 | 66.39 | 243.52 |
+| | Diffusers | 1 | 9.00 | 74.00 | 275.20 |
+| | TensorRT-LLM | — | | | |
+| | NIM | 1 | 6.25 | 58.64 | 232.47 |
+| **H100 80GB HBM3** | PyTorch | 1 | 7.64 | 59.95 | 207.87 |
+| | vLLM-Omni | 1 | 7.37 | 59.77 | 205.97 |
+| | Diffusers | 1 | 9.00 | 68.00 | 239.80 |
+| | TensorRT-LLM | 1 | 6.90 | 63.24 | 226.15 |
+| | NIM | 1 | 6.08 | 53.02 | 202.59 |
+| **H200 141GB HBM3** | PyTorch | 1 | 7.65 | 60.51 | 214.80 |
+| | vLLM-Omni | 1 | 7.28 | 59.64 | 209.65 |
+| | Diffusers | 1 | 9.00 | 67.20 | 240.00 |
+| | TensorRT-LLM | 1 | 6.74 | 63.54 | 231.15 |
+| | NIM | 1 | 6.04 | 53.25 | 203.66 |
+| **B200** | PyTorch | 1 | 4.60 | 33.08 | 113.90 |
+| | vLLM-Omni | 1 | 4.33 | 33.09 | 110.08 |
+| | Diffusers | 1 | 7.00 | 37.00 | 116.00 |
+| | TensorRT-LLM | 1 | 3.70 | 29.33 | 102.35 |
+| | NIM | 1 | 4.05 | 27.72 | 95.57 |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | 5.61 | 33.45 | 104.75 |
+| | Diffusers | 1 | 13.40 | 49.59 | 131.25 |
+| | TensorRT-LLM | 1 | 3.70 | 27.73 | 93.88 |
+| | NIM | 1 | 4.50 | 28.90 | 92.59 |
+
+### Text-to-Image (t2i)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 2.99 | 4.51 | 7.12 |
+| | vLLM-Omni | 1 | 1.59 | 2.87 | 4.99 |
+| | Diffusers | 1 | 2.00 | 4.00 | 5.00 |
+| | TensorRT-LLM | 1 | 1.18 | 2.35 | 4.50 |
+| **H20** | PyTorch | 1 | 3.06 | 6.51 | 12.31 |
+| | vLLM-Omni | 1 | 1.73 | 4.92 | 10.73 |
+| | Diffusers | 1 | 3.00 | 6.00 | 10.00 |
+| | TensorRT-LLM | 1 | 1.94 | 5.55 | 11.56 |
+| **H100 NVL** | PyTorch | 1 | 2.77 | 2.83 | 4.21 |
+| | vLLM-Omni | 1 | 1.55 | 1.92 | 3.43 |
+| | Diffusers | 1 | 3.00 | 3.00 | 4.00 |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 1 | 2.75 | 2.85 | 3.58 |
+| | vLLM-Omni | 1 | 1.53 | 1.58 | 2.81 |
+| | Diffusers | 1 | 3.00 | 3.00 | 4.00 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 3.01 | 3.01 | 3.45 |
+| | vLLM-Omni | 1 | 1.61 | 1.53 | 2.61 |
+| | Diffusers | 1 | 3.00 | 3.00 | 4.00 |
+| | TensorRT-LLM | 1 | 1.02 | 1.30 | 2.63 |
+| **H200 141GB HBM3** | PyTorch | 1 | 2.96 | 3.04 | 3.28 |
+| | vLLM-Omni | 1 | 1.57 | 1.52 | 2.60 |
+| | Diffusers | 1 | 3.00 | 3.00 | 4.00 |
+| | TensorRT-LLM | 1 | 1.05 | 1.30 | 2.60 |
+| **B200** | PyTorch | 1 | 2.68 | 2.75 | 2.87 |
+| | vLLM-Omni | 1 | 1.49 | 1.20 | 1.76 |
+| | Diffusers | 1 | 3.00 | 3.20 | 3.00 |
+| | TensorRT-LLM | 1 | 0.86 | 0.88 | 1.40 |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | 1.97 | 1.81 | 2.34 |
+| | Diffusers | 1 | 3.86 | 3.86 | 3.99 |
+| | TensorRT-LLM | 1 | 1.36 | 1.30 | 1.40 |
+
+Notes:
+1. All times measured on identical workloads (same seed, sampler settings, prompt).
+2. Multi-GPU configurations use tensor parallelism, except TensorRT-LLM, which may also split across CFG and Ulysses dimensions.
+3. vLLM-Omni numbers are for the upcoming public release in the vLLM-Omni repo and are subject to change before GA; the H100 NVL values in particular are pre-release.
+4. Diffusers numbers use the HuggingFace `diffusers` integration without custom CUDA graphs. Single-GPU values come from PBR `#308202` and PBR `#308451`; multi-GPU values from PBR `#308918`.
+5. PyTorch numbers report average generation (sampling) time from OSS inference benchmarking.
+6. At 256p, multi-GPU configurations on B300 may underperform single-GPU because of small-workload tensor-parallel overhead, so single-GPU is the recommended deployment at this resolution.
+7. NIM numbers use latency profiles with FP8 precision and report end-to-end `Request Latency s`, including request processing, video generation, output encoding, and returning the response.
+
+## Additional audiovisual generation
+
+### Video-to-Video (v2v)
+
+A text prompt and source video condition a generated continuation or transformation.
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 13.73 | 180.54 | 785.41 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 24.19 | 135.85 | 432.18 |
+| | TensorRT-LLM | 1 | 10.36 | 102.50 | 370.24 |
+| **H20** | PyTorch | 1 | 30.44 | 257.79 | 930.96 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 44.88 | 287.55 | 974.75 |
+| | TensorRT-LLM | 1 | 27.10 | 250.57 | 908.07 |
+| **H100 NVL** | PyTorch | 1 | 10.18 | 81.73 | 297.83 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 23.66 | 107.79 | 354.66 |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 1 | 8.10 | 69.70 | 250.33 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 21.40 | 96.52 | 313.13 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 7.50 | 59.75 | 207.36 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 19.48 | 86.51 | 267.90 |
+| | TensorRT-LLM | 1 | 6.63 | 60.18 | 229.04 |
+| **H200 141GB HBM3** | PyTorch | 1 | 7.48 | 60.23 | 214.03 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 18.93 | 85.52 | 266.84 |
+| | TensorRT-LLM | 1 | 6.59 | 61.40 | 229.48 |
+| **B200** | PyTorch | 1 | 4.52 | 32.53 | 114.16 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 16.93 | 52.32 | 137.54 |
+| | TensorRT-LLM | 1 | 3.54 | 28.37 | 100.29 |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 16.14 | 50.74 | 131.11 |
+| | TensorRT-LLM | 1 | 3.44 | 26.63 | 91.40 |
+
+### Text-to-Audio-and-Video (t2av)
+
+A text prompt produces synchronized video and sound.
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 14.13 | 180.98 | 794.74 |
+| | vLLM-Omni | 1 | 12.25 | 106.02 | 373.10 |
+| | Diffusers | 1 | 13.00 | 113.00 | 393.00 |
+| | TensorRT-LLM | 1 | 11.35 | 103.28 | 374.75 |
+| **H20** | PyTorch | 1 | 30.82 | 256.41 | 922.35 |
+| | vLLM-Omni | 1 | 29.43 | 260.84 | 937.93 |
+| | Diffusers | 1 | 32.00 | 263.00 | 932.60 |
+| | TensorRT-LLM | 1 | 29.38 | 254.88 | 913.33 |
+| **H100 NVL** | PyTorch | 1 | 9.99 | 82.32 | 297.88 |
+| | vLLM-Omni | 1 | 9.92 | 81.57 | 291.91 |
+| | Diffusers | 1 | 12.00 | 91.00 | 324.60 |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 1 | 8.20 | 69.88 | 250.46 |
+| | vLLM-Omni | 1 | 7.82 | 65.42 | 244.60 |
+| | Diffusers | 1 | 10.00 | 75.00 | 277.80 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 7.60 | 59.09 | 207.87 |
+| | vLLM-Omni | 1 | 7.34 | 58.65 | 203.92 |
+| | Diffusers | 1 | 9.40 | 69.00 | 242.00 |
+| | TensorRT-LLM | 1 | 7.04 | 61.09 | 228.06 |
+| **H200 141GB HBM3** | PyTorch | 1 | 7.55 | 60.17 | 211.59 |
+| | vLLM-Omni | 1 | 7.13 | 58.27 | 209.29 |
+| | Diffusers | 1 | 9.00 | 69.00 | 237.00 |
+| | TensorRT-LLM | 1 | 6.93 | 60.77 | 233.06 |
+| **B200** | PyTorch | 1 | 4.63 | 32.60 | 113.89 |
+| | vLLM-Omni | 1 | 4.29 | 32.20 | 107.74 |
+| | Diffusers | 1 | 7.00 | 37.00 | 117.00 |
+| | TensorRT-LLM | 1 | 3.77 | 28.64 | 101.28 |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | 5.59 | 33.15 | 104.92 |
+| | Diffusers | 1 | 6.46 | 39.66 | 122.33 |
+| | TensorRT-LLM | 1 | 3.65 | 26.83 | 91.85 |
+
+### Video-to-Audio-and-Video (v2av)
+
+A text prompt and source video produce transformed video with synchronized sound.
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 13.73 | 180.72 | 786.11 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 26.30 | 135.47 | 429.61 |
+| | TensorRT-LLM | — | | | |
+| **H20** | PyTorch | 1 | 30.42 | 257.83 | 921.82 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 46.72 | 288.98 | 985.80 |
+| | TensorRT-LLM | — | | | |
+| **H100 NVL** | PyTorch | 1 | 9.91 | 81.96 | 297.51 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 22.95 | 110.93 | 354.02 |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 1 | 8.10 | 69.59 | 246.51 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 22.19 | 94.85 | 314.06 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 7.49 | 59.86 | 207.55 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 21.73 | 88.42 | 268.93 |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | 1 | 7.49 | 60.15 | 214.44 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 17.98 | 87.84 | 267.54 |
+| | TensorRT-LLM | — | | | |
+| **B200** | PyTorch | 1 | 4.51 | 32.62 | 113.72 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 15.64 | 50.57 | 138.15 |
+| | TensorRT-LLM | — | | | |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 15.93 | 51.87 | 131.52 |
+| | TensorRT-LLM | — | | | |
+
+### Image-to-Audio-and-Video (i2av)
+
+A text prompt and source image produce video with synchronized sound.
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 14.08 | 181.64 | 787.81 |
+| | vLLM-Omni | 1 | 12.61 | 108.05 | 378.04 |
+| | Diffusers | 1 | 14.00 | 113.00 | 393.00 |
+| | TensorRT-LLM | 1 | 11.85 | 105.53 | 379.62 |
+| **H20** | PyTorch | 1 | 31.34 | 259.06 | 924.39 |
+| | vLLM-Omni | 1 | 30.36 | 265.37 | 948.09 |
+| | Diffusers | 1 | 32.00 | 263.00 | 934.80 |
+| | TensorRT-LLM | 1 | 29.95 | 259.43 | 924.85 |
+| **H100 NVL** | PyTorch | 1 | 10.45 | 84.37 | 298.61 |
+| | vLLM-Omni | 1 | 10.34 | 83.21 | 295.65 |
+| | Diffusers | 1 | 12.00 | 91.00 | 324.40 |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 1 | 8.29 | 71.20 | 248.35 |
+| | vLLM-Omni | 1 | 8.24 | 67.23 | 249.41 |
+| | Diffusers | 1 | 10.00 | 75.00 | 277.20 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 7.73 | 59.13 | 207.93 |
+| | vLLM-Omni | 1 | 7.74 | 60.27 | 207.53 |
+| | Diffusers | 1 | 10.00 | 69.00 | 241.00 |
+| | TensorRT-LLM | 1 | 7.39 | 62.91 | 227.42 |
+| **H200 141GB HBM3** | PyTorch | 1 | 7.66 | 60.55 | 214.82 |
+| | vLLM-Omni | 1 | 7.55 | 59.73 | 212.73 |
+| | Diffusers | 1 | 9.00 | 68.00 | 241.00 |
+| | TensorRT-LLM | 1 | 7.37 | 62.87 | 231.61 |
+| **B200** | PyTorch | 1 | 4.62 | 32.82 | 113.85 |
+| | vLLM-Omni | 1 | 4.58 | 33.36 | 110.05 |
+| | Diffusers | 1 | 7.20 | 37.00 | 118.00 |
+| | TensorRT-LLM | 1 | 4.04 | 29.77 | 103.28 |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | 6.01 | 34.39 | 108.59 |
+| | Diffusers | 1 | 15.35 | 50.19 | 131.92 |
+| | TensorRT-LLM | 1 | 4.03 | 28.10 | 94.57 |
+
+## Transfer generation
+
+Transfer conditions a video-to-video generation on a structural control hint
+extracted from the source video. Each control is reported separately because
+the hint changes how much of the frame the model must synthesise.
+
+| GPU | Transfer control | Engine | GPUs | 256p | 480p | 720p |
+|---|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | blur | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 40.11 | 288.60 | 1061.44 |
+| | | Diffusers | 1 | 30.95 | 217.40 | 735.43 |
+| | | TensorRT-LLM | 1 | 25.62 | 249.50 | 935.86 |
+| | | NIM | 1 | | | |
+| | depth | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 31.56 | 291.76 | 1090.33 |
+| | | Diffusers | 1 | 36.52 | 225.34 | 745.70 |
+| | | TensorRT-LLM | 1 | 26.13 | 253.94 | 942.69 |
+| | | NIM | 1 | | | |
+| | edge | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 30.64 | 287.82 | 1080.82 |
+| | | Diffusers | 1 | 31.25 | 217.90 | 735.35 |
+| | | TensorRT-LLM | 1 | 25.67 | 250.54 | 938.79 |
+| | | NIM | 1 | | | |
+| | multi_control | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 73.36 | 1060.11 | 3988.93 |
+| | | Diffusers | 1 | | | |
+| | | TensorRT-LLM | 1 | 35.07 | 423.61 | 1745.86 |
+| | | NIM | 1 | | | |
+| | seg | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 31.50 | 289.01 | 1083.64 |
+| | | Diffusers | 1 | 32.89 | 220.10 | 738.51 |
+| | | TensorRT-LLM | 1 | 25.85 | 250.47 | 937.18 |
+| | | NIM | 1 | | | |
+| | wsm | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 26.12 | 225.70 | 814.25 |
+| | | Diffusers | 1 | 29.84 | 176.06 | 565.32 |
+| | | TensorRT-LLM | 1 | 12.95 | 114.91 | 407.62 |
+| | | NIM | 1 | | | |
+| **H20** | blur | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 85.93 | 625.60 | 2280.10 |
+| | | Diffusers | 1 | 73.61 | 491.22 | 1726.61 |
+| | | TensorRT-LLM | 1 | 63.10 | 614.14 | 2308.16 |
+| | | NIM | 1 | | | |
+| | depth | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 66.69 | 636.40 | 2367.37 |
+| | | Diffusers | 1 | 86.84 | 510.15 | 1753.96 |
+| | | TensorRT-LLM | 1 | 64.44 | 622.79 | 2328.65 |
+| | | NIM | 1 | | | |
+| | edge | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 64.75 | 626.76 | 2321.00 |
+| | | Diffusers | 1 | 74.68 | 492.78 | 1728.26 |
+| | | TensorRT-LLM | 1 | 63.92 | 615.09 | 2310.55 |
+| | | NIM | 1 | | | |
+| | multi_control | PyTorch | 8 | | | |
+| | | vLLM-Omni | 8 | 60.40 | | 2622.35 |
+| | | Diffusers | 8 | | | |
+| | | TensorRT-LLM | 8 | 0.64 | 0.54 | 0.51 |
+| | | NIM | 8 | | | |
+| | seg | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 65.84 | 623.52 | 2341.06 |
+| | | Diffusers | 1 | 77.50 | 496.77 | 1734.77 |
+| | | TensorRT-LLM | 1 | 63.56 | 616.74 | 2314.38 |
+| | | NIM | 1 | | | |
+| | wsm | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 53.66 | 488.58 | 1753.23 |
+| | | Diffusers | 1 | 70.42 | 398.67 | 1319.24 |
+| | | TensorRT-LLM | 1 | 32.09 | 284.19 | 1001.59 |
+| | | NIM | 1 | | | |
+| **H100 NVL** | blur | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 27.53 | 184.34 | 684.44 |
+| | | Diffusers | 1 | 26.97 | 224.61 | 775.61 |
+| | | TensorRT-LLM | 1 | | | |
+| | | NIM | 1 | | | |
+| | depth | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 20.73 | 191.19 | 683.55 |
+| | | Diffusers | 1 | 31.63 | 233.03 | 610.83 |
+| | | TensorRT-LLM | 1 | | | |
+| | | NIM | 1 | | | |
+| | edge | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 20.32 | 188.64 | 674.49 |
+| | | Diffusers | 1 | 34.73 | 173.04 | 602.04 |
+| | | TensorRT-LLM | 1 | | | |
+| | | NIM | 1 | | | |
+| | multi_control | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 50.16 | 674.18 | 2999.04 |
+| | | Diffusers | 1 | | | |
+| | | TensorRT-LLM | 1 | | | |
+| | | NIM | 1 | | | |
+| | seg | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 20.87 | 190.35 | 680.37 |
+| | | Diffusers | 1 | 28.55 | 174.78 | 777.58 |
+| | | TensorRT-LLM | 1 | | | |
+| | | NIM | 1 | | | |
+| | wsm | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 17.17 | 148.32 | 507.19 |
+| | | Diffusers | 1 | 26.17 | 139.82 | 594.21 |
+| | | TensorRT-LLM | 1 | | | |
+| | | NIM | 1 | | | |
+| **H100 80GB HBM3** | blur | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 20.40 | 133.27 | 476.11 |
+| | | Diffusers | 1 | 21.06 | 131.86 | 454.46 |
+| | | TensorRT-LLM | 1 | 15.20 | 149.57 | 575.59 |
+| | | NIM | 1 | | | |
+| | depth | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 15.75 | 135.11 | 488.18 |
+| | | Diffusers | 1 | 24.61 | 135.88 | 457.43 |
+| | | TensorRT-LLM | 1 | 15.45 | 149.96 | 580.66 |
+| | | NIM | 1 | | | |
+| | edge | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 15.33 | 133.00 | 483.75 |
+| | | Diffusers | 1 | 21.28 | 132.06 | 447.24 |
+| | | TensorRT-LLM | 1 | 15.28 | 148.99 | 572.91 |
+| | | NIM | 1 | | | |
+| | multi_control | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 36.94 | 477.12 | 2122.18 |
+| | | Diffusers | 1 | | | |
+| | | TensorRT-LLM | 1 | 21.50 | 254.29 | 1072.98 |
+| | | NIM | 1 | | | |
+| | seg | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 16.04 | 133.82 | 484.97 |
+| | | Diffusers | 1 | 22.54 | 133.24 | 456.55 |
+| | | TensorRT-LLM | 1 | 15.42 | 145.46 | 576.57 |
+| | | NIM | 1 | | | |
+| | wsm | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 13.03 | 105.20 | 365.05 |
+| | | Diffusers | 1 | 20.25 | 106.79 | 342.79 |
+| | | TensorRT-LLM | 1 | 7.96 | 68.97 | 248.27 |
+| | | NIM | 1 | | | |
+| **H200 NVL** | blur | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 21.94 | 156.49 | 586.19 |
+| | | Diffusers | 1 | 22.82 | 152.13 | 535.83 |
+| | | TensorRT-LLM | 1 | | | |
+| | | NIM | 1 | | | |
+| | depth | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 16.93 | 159.81 | 597.37 |
+| | | Diffusers | 1 | 26.80 | 156.98 | 541.71 |
+| | | TensorRT-LLM | 1 | | | |
+| | | NIM | 1 | | | |
+| | edge | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 16.46 | 157.29 | 592.05 |
+| | | Diffusers | 1 | 23.06 | 152.54 | 533.87 |
+| | | TensorRT-LLM | 1 | | | |
+| | | NIM | 1 | | | |
+| | multi_control | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 40.28 | 587.45 | 2792.29 |
+| | | Diffusers | 1 | | | |
+| | | TensorRT-LLM | 1 | | | |
+| | | NIM | 1 | | | |
+| | seg | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 17.13 | 157.81 | 594.45 |
+| | | Diffusers | 1 | 24.12 | 153.68 | 537.15 |
+| | | TensorRT-LLM | 1 | | | |
+| | | NIM | 1 | | | |
+| | wsm | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 13.97 | 122.69 | 442.62 |
+| | | Diffusers | 1 | 21.90 | 123.08 | 407.57 |
+| | | TensorRT-LLM | 1 | | | |
+| | | NIM | 1 | | | |
+| **H200 141GB HBM3** | blur | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 20.78 | 134.95 | 492.24 |
+| | | Diffusers | 1 | 20.63 | 128.41 | 450.79 |
+| | | TensorRT-LLM | 1 | 15.11 | 149.55 | 580.80 |
+| | | NIM | 1 | | | |
+| | depth | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 16.00 | 138.25 | 497.13 |
+| | | Diffusers | 1 | 24.01 | 134.51 | 457.91 |
+| | | TensorRT-LLM | 1 | 15.42 | 152.64 | 587.03 |
+| | | NIM | 1 | | | |
+| | edge | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 15.26 | 136.41 | 492.75 |
+| | | Diffusers | 1 | 20.87 | 130.99 | 443.92 |
+| | | TensorRT-LLM | 1 | 14.95 | 148.90 | 586.42 |
+| | | NIM | 1 | | | |
+| | multi_control | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 38.09 | 500.91 | 2316.90 |
+| | | Diffusers | 1 | | | |
+| | | TensorRT-LLM | 1 | 21.65 | 259.30 | 1095.79 |
+| | | NIM | 1 | | | |
+| | seg | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 16.03 | 136.90 | 493.89 |
+| | | Diffusers | 1 | 21.84 | 130.12 | 453.51 |
+| | | TensorRT-LLM | 1 | 15.31 | 148.26 | 583.48 |
+| | | NIM | 1 | | | |
+| | wsm | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 12.95 | 109.39 | 371.24 |
+| | | Diffusers | 1 | 19.65 | 106.00 | 344.09 |
+| | | TensorRT-LLM | 1 | 7.90 | 68.71 | 252.43 |
+| | | NIM | 1 | | | |
+| **B200** | blur | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 13.26 | 72.95 | 257.39 |
+| | | Diffusers | 1 | 12.69 | 70.78 | 226.51 |
+| | | TensorRT-LLM | 1 | 7.73 | 68.21 | 252.69 |
+| | | NIM | 1 | | | |
+| | depth | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 10.55 | 73.56 | 264.11 |
+| | | Diffusers | 1 | 14.79 | 73.23 | 229.54 |
+| | | TensorRT-LLM | 1 | 7.92 | 68.77 | 248.98 |
+| | | NIM | 1 | | | |
+| | edge | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 10.35 | 74.00 | 261.85 |
+| | | Diffusers | 1 | 12.76 | 71.04 | 223.24 |
+| | | TensorRT-LLM | 1 | 7.78 | 68.29 | 248.51 |
+| | | NIM | 1 | | | |
+| | multi_control | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 23.27 | 257.99 | 1111.03 |
+| | | Diffusers | 1 | | | |
+| | | TensorRT-LLM | 1 | 10.72 | 112.58 | 455.44 |
+| | | NIM | 1 | | | |
+| | seg | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 11.10 | 73.35 | 262.72 |
+| | | Diffusers | 1 | 13.54 | 71.21 | 223.41 |
+| | | TensorRT-LLM | 1 | 7.99 | 68.45 | 248.75 |
+| | | NIM | 1 | | | |
+| | wsm | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 9.41 | 59.04 | 195.99 |
+| | | Diffusers | 1 | 12.16 | 59.29 | 172.60 |
+| | | TensorRT-LLM | 1 | 4.25 | 32.24 | 108.75 |
+| | | NIM | 1 | | | |
+| **B300** | blur | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 13.85 | 73.35 | 240.39 |
+| | | Diffusers | 1 | 12.39 | 66.13 | 207.59 |
+| | | TensorRT-LLM | 1 | 7.67 | 62.95 | 228.34 |
+| | | NIM | 1 | | | |
+| | depth | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 11.11 | 71.59 | 247.16 |
+| | | Diffusers | 1 | 14.26 | 70.00 | 211.12 |
+| | | TensorRT-LLM | 1 | 7.67 | 63.68 | 226.26 |
+| | | NIM | 1 | | | |
+| | edge | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 13.05 | 72.93 | 245.16 |
+| | | Diffusers | 1 | 12.48 | 67.68 | 207.95 |
+| | | TensorRT-LLM | 1 | 7.58 | 63.10 | 228.36 |
+| | | NIM | 1 | | | |
+| | multi_control | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 26.79 | 243.97 | 1026.91 |
+| | | Diffusers | 1 | | | |
+| | | TensorRT-LLM | 1 | 10.59 | 105.33 | 414.58 |
+| | | NIM | 1 | | | |
+| | seg | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 14.38 | 71.85 | 246.04 |
+| | | Diffusers | 1 | 13.43 | 68.85 | 210.33 |
+| | | TensorRT-LLM | 1 | 7.64 | 64.13 | 228.37 |
+| | | NIM | 1 | | | |
+| | wsm | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 10.06 | 58.97 | 185.08 |
+| | | Diffusers | 1 | 11.95 | 55.41 | 162.28 |
+| | | TensorRT-LLM | 1 | 4.23 | 30.44 | 101.17 |
+| | | NIM | 1 | | | |
+
+Transfer notes:
+1. Values are average generation latency in seconds; lower is better. Diffusers numbers come from PBR `#308587`, vLLM-Omni from PBR `#308574`, and TensorRT-LLM from PBR `#308000`.
+2. The **GPUs** column gives the number of GPUs behind every value in that row, and is the same for every engine in a GPU block so the rows can be compared directly.
+3. PyTorch and NIM have no transfer coverage yet; those rows are unmeasured, not unsupported.
+4. Control hints follow the vLLM-Omni `extra_params` names: `blur`, `depth`, `edge`, `multi_control`, `seg`, and `wsm`. `multi_control` combines several hints in one request.
+
+## Action generation
+
+Forward dynamics is reported separately for AV, camera, and robot inputs. Inverse dynamics and policy are reported for AV and robot because those are the only domain rows in PBR `#308197`; no camera row is inferred. For each domain, PyTorch is populated from that report. vLLM-Omni currently covers forward dynamics AV and inverse dynamics AV from PBR `#308481`. Camera, robot-FD, robot-ID, policy-AV, and policy-robot vLLM-Omni rows remain reserved. **Policy — DROID** is a separate checkpoint (`nvidia/Cosmos3-Nano-Policy-DROID`) and is not mixed with the policy-robot table.
+
+### Forward Dynamics — Autonomous Vehicle (AV)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 16.87 | 16.86 | 16.85 |
+| | vLLM-Omni | 1 | 2.08 | 12.94 | 36.19 |
+| | Diffusers | 1 | 2.00 | 12.00 | 12.00 |
+| | TensorRT-LLM | — | | | |
+| **H20** | PyTorch | 1 | 31.47 | 31.16 | 31.45 |
+| | vLLM-Omni | 1 | 4.82 | 31.36 | 87.55 |
+| | Diffusers | 1 | 5.00 | 28.00 | 28.20 |
+| | TensorRT-LLM | — | | | |
+| **H100 NVL** | PyTorch | 1 | 10.32 | 10.66 | 10.64 |
+| | vLLM-Omni | 1 | 1.71 | 10.58 | 28.26 |
+| | Diffusers | 1 | 2.00 | 10.00 | 10.00 |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 1 | 8.30 | 8.31 | 8.33 |
+| | vLLM-Omni | 1 | 1.43 | 8.21 | 22.78 |
+| | Diffusers | 1 | 2.00 | 8.00 | 8.00 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 7.80 | 7.87 | 7.79 |
+| | vLLM-Omni | 1 | 1.33 | 7.74 | 20.60 |
+| | Diffusers | 1 | 2.00 | 8.00 | 8.00 |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | 1 | 7.77 | 7.76 | 7.81 |
+| | vLLM-Omni | 1 | 1.33 | 7.72 | 20.65 |
+| | Diffusers | 1 | 2.00 | 8.00 | 8.00 |
+| | TensorRT-LLM | — | | | |
+| **B200** | PyTorch | 1 | 4.75 | 4.75 | 4.73 |
+| | vLLM-Omni | 1 | 0.94 | 4.93 | 12.00 |
+| | Diffusers | 1 | 2.00 | 5.00 | 5.00 |
+| | TensorRT-LLM | — | | | |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | 1.09 | 4.86 | 11.70 |
+| | Diffusers | 1 | 20.87 | 24.49 | 26.44 |
+| | TensorRT-LLM | — | | | |
+
+### Forward Dynamics — Camera
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 16.82 | 16.82 | 16.81 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H20** | PyTorch | 1 | 31.40 | 31.10 | 31.40 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H100 NVL** | PyTorch | 1 | 10.61 | 10.32 | 10.57 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 1 | 8.24 | 8.26 | 8.26 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 7.78 | 7.83 | 7.75 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | 1 | 7.73 | 7.75 | 7.75 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **B200** | PyTorch | 1 | 4.70 | 4.74 | 4.71 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+
+### Forward Dynamics — Robot
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 3.74 | 3.73 | 3.72 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 3.00 | 3.00 |
+| | TensorRT-LLM | — | | | |
+| **H20** | PyTorch | 1 | 7.00 | 7.01 | 7.01 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 3.00 | 7.00 | 7.00 |
+| | TensorRT-LLM | — | | | |
+| **H100 NVL** | PyTorch | 1 | 2.49 | 2.50 | 2.55 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 3.00 | 3.00 |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 1 | 2.08 | 2.09 | 2.09 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 3.00 | 3.00 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 2.00 | 2.01 | 1.98 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 3.00 | 3.00 |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | 1 | 1.93 | 1.93 | 1.93 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 2.00 | 2.00 |
+| | TensorRT-LLM | — | | | |
+| **B200** | PyTorch | 1 | 1.28 | 1.30 | 1.31 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 2.00 | 2.00 |
+| | TensorRT-LLM | — | | | |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 22.65 | 20.75 | 18.10 |
+| | TensorRT-LLM | — | | | |
+
+### Inverse Dynamics — Autonomous Vehicle (AV)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 16.74 | 16.75 | 16.75 |
+| | vLLM-Omni | 1 | 2.10 | 12.96 | 36.10 |
+| | Diffusers | 1 | 2.00 | 12.00 | 12.00 |
+| | TensorRT-LLM | — | | | |
+| **H20** | PyTorch | 1 | 31.22 | 30.99 | 31.22 |
+| | vLLM-Omni | 1 | 4.84 | 31.36 | 87.50 |
+| | Diffusers | 1 | 5.00 | 28.00 | 28.00 |
+| | TensorRT-LLM | — | | | |
+| **H100 NVL** | PyTorch | 1 | 10.47 | 10.45 | 10.44 |
+| | vLLM-Omni | 1 | 1.74 | 10.54 | 28.16 |
+| | Diffusers | 1 | 2.00 | 10.00 | 10.00 |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 1 | 8.12 | 8.13 | 8.10 |
+| | vLLM-Omni | 1 | 1.46 | 8.20 | 22.34 |
+| | Diffusers | 1 | 2.00 | 8.00 | 8.00 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 7.62 | 7.63 | 7.68 |
+| | vLLM-Omni | 1 | 1.39 | 7.72 | 20.55 |
+| | Diffusers | 1 | 2.00 | 8.00 | 8.00 |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | 1 | 7.51 | 7.64 | 7.51 |
+| | vLLM-Omni | 1 | 1.36 | 7.69 | 20.65 |
+| | Diffusers | 1 | 2.00 | 8.00 | 8.00 |
+| | TensorRT-LLM | — | | | |
+| **B200** | PyTorch | 1 | 4.60 | 4.63 | 4.58 |
+| | vLLM-Omni | 1 | 0.92 | 5.10 | 12.29 |
+| | Diffusers | 1 | 2.00 | 5.00 | 5.00 |
+| | TensorRT-LLM | — | | | |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | 1.36 | 5.75 | 11.89 |
+| | Diffusers | 1 | 8.76 | 17.79 | 17.99 |
+| | TensorRT-LLM | — | | | |
+
+### Inverse Dynamics — Robot
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 3.70 | 3.70 | 3.70 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 3.00 | 3.00 |
+| | TensorRT-LLM | — | | | |
+| **H20** | PyTorch | 1 | 6.94 | 6.94 | 6.89 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 3.00 | 7.00 | 7.00 |
+| | TensorRT-LLM | — | | | |
+| **H100 NVL** | PyTorch | 1 | 2.53 | 2.47 | 2.54 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 3.00 | 3.00 |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 1 | 2.05 | 2.05 | 2.05 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 3.00 | 3.00 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 1.96 | 1.96 | 1.95 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 3.00 | 3.00 |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | 1 | 1.90 | 1.90 | 1.91 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 2.20 | 2.00 |
+| | TensorRT-LLM | — | | | |
+| **B200** | PyTorch | 1 | 1.28 | 1.27 | 1.28 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 2.00 | 2.00 |
+| | TensorRT-LLM | — | | | |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 9.28 | 12.40 | 10.86 |
+| | TensorRT-LLM | — | | | |
+
+### Policy — Autonomous Vehicle (AV)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 16.88 | 16.89 | 16.91 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 12.00 | 12.00 |
+| | TensorRT-LLM | — | | | |
+| **H20** | PyTorch | 1 | 31.51 | 31.51 | 31.50 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 5.00 | 28.60 | 28.40 |
+| | TensorRT-LLM | — | | | |
+| **H100 NVL** | PyTorch | 1 | 10.66 | 10.65 | 10.35 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 10.00 | 10.00 |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 1 | 8.31 | 8.32 | 8.31 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 8.00 | 8.00 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 7.82 | 7.82 | 7.80 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 8.00 | 8.00 |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | 1 | 7.76 | 7.69 | 7.66 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 8.00 | 8.00 |
+| | TensorRT-LLM | — | | | |
+| **B200** | PyTorch | 1 | 4.75 | 4.77 | 4.74 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 5.00 | 5.00 |
+| | TensorRT-LLM | — | | | |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 13.11 | 18.21 | 16.49 |
+| | TensorRT-LLM | — | | | |
+
+### Policy — Robot
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 3.74 | 3.74 | 3.74 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 3.00 | 3.00 |
+| | TensorRT-LLM | — | | | |
+| **H20** | PyTorch | 1 | 6.95 | 7.00 | 7.01 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 3.00 | 7.00 | 7.00 |
+| | TensorRT-LLM | — | | | |
+| **H100 NVL** | PyTorch | 1 | 2.50 | 2.51 | 2.55 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 3.00 | 3.00 |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 1 | 2.11 | 2.09 | 2.09 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 3.00 | 3.00 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 1.99 | 1.99 | 1.99 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 3.00 | 3.00 |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | 1 | 1.93 | 1.93 | 1.94 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 2.00 | 2.20 |
+| | TensorRT-LLM | — | | | |
+| **B200** | PyTorch | 1 | 1.30 | 1.30 | 1.30 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 2.00 | 2.00 | 2.00 |
+| | TensorRT-LLM | — | | | |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 10.62 | 12.78 | 11.00 |
+| | TensorRT-LLM | — | | | |
+
+### Policy — DROID
+
+These rows report **Cosmos3-Nano-Policy-DROID**, not the general Cosmos3-Nano checkpoint used in the other action tables. vLLM-Omni only supports this modality at **480p on one GPU** (multi-GPU is disabled, and resolution is fixed for the multiview wrist/exterior inputs). PyTorch and Diffusers cells are reserved.
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | | 3.82 | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H20** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | | 8.51 | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H100 NVL** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | | 2.94 | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | | 2.34 | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | | 2.23 | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | | 2.21 | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **B200** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | | 1.47 | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | | 2.15 | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+
+Additional-modality notes:
+1. PyTorch values are average generation (sampling) latency in seconds from PBR `#308197`; lower is better.
+2. PyTorch values use `CUDA_GRAPH=No` and the `latency` automatic-sharding preset.
+3. vLLM-Omni audiovisual values for `t2av`/`t2vs` and `i2av`/`i2vs` are from PBR `#308195`. vLLM-Omni action values are from PBR `#308481`.
+4. Action vLLM-Omni rows report one GPU because the 8-GPU Ulysses runs failed sequence-length divisibility checks.
+5. Policy-DROID vLLM-Omni uses the `nvidia/Cosmos3-Nano-Policy-DROID` checkpoint at 480p on one GPU only. It is reported in its own table and is not comparable to the PyTorch policy-robot row.
+6. Diffusers rows are intentionally empty reservations for future benchmark campaigns.
+7. The **GPUs** column gives the number of GPUs behind every value in that row.
+8. Empty cells indicate unmeasured combinations, not unsupported combinations.
\ No newline at end of file
diff --git a/inference_benchmarks/cosmos3-super-fp8-generator.md b/inference_benchmarks/cosmos3-super-fp8-generator.md
new file mode 100644
index 00000000..75b34a6d
--- /dev/null
+++ b/inference_benchmarks/cosmos3-super-fp8-generator.md
@@ -0,0 +1,433 @@
+# Cosmos3-Super-FP8 Generator Inference Benchmarks
+
+[Back to the inference benchmark index](../inference_benchmarks.md)
+
+These tables report **Cosmos3-Super-FP8** Generator latency in seconds, for the FP8 quantized Cosmos3-Super checkpoint. Lower is better. The BF16 numbers for the same model are on the [Cosmos3-Super page](cosmos3-super-generator.md).
+
+Every row reports one GPU configuration, named in the **GPUs** column, and all three resolutions in that row come from it. The configuration is one GPU when the model fits on a single device at its highest resolution, 720p, and eight GPUs when it does not. Within one GPU's block every engine reports the same configuration, so a column can be read straight across the runtimes. Cosmos3-Super-FP8 fits on a single GPU except on H100 80GB HBM3, where the 720p runs need eight.
+
+Empty cells mean that a run has not been completed for that GPU, engine, or resolution; they do not indicate that a combination is unsupported.
+
+## Table of Contents
+
+- [Benchmark methodology](#benchmark-methodology)
+- [Workload definitions](#workload-definitions)
+- [Primary vision generation](#primary-vision-generation)
+ - [Text-to-Video (t2v)](#text-to-video-t2v)
+ - [Image-to-Video (i2v)](#image-to-video-i2v)
+ - [Text-to-Image (t2i)](#text-to-image-t2i)
+- [Additional audiovisual generation](#additional-audiovisual-generation)
+ - [Video-to-Video (v2v)](#video-to-video-v2v)
+ - [Text-to-Audio-and-Video (t2av)](#text-to-audio-and-video-t2av)
+ - [Video-to-Audio-and-Video (v2av)](#video-to-audio-and-video-v2av)
+ - [Image-to-Audio-and-Video (i2av)](#image-to-audio-and-video-i2av)
+- [Transfer generation](#transfer-generation)
+- [Action generation](#action-generation)
+ - [Forward Dynamics — Autonomous Vehicle (AV)](#forward-dynamics--autonomous-vehicle-av)
+ - [Forward Dynamics — Camera](#forward-dynamics--camera)
+ - [Forward Dynamics — Robot](#forward-dynamics--robot)
+ - [Inverse Dynamics — Autonomous Vehicle (AV)](#inverse-dynamics--autonomous-vehicle-av)
+ - [Inverse Dynamics — Robot](#inverse-dynamics--robot)
+ - [Policy — Autonomous Vehicle (AV)](#policy--autonomous-vehicle-av)
+ - [Policy — Robot](#policy--robot)
+
+## Benchmark methodology
+
+PyTorch values are from PBR `#309161`, **FP8 Cosmos3-Nano/Super (regular non-distilled) Generator PyTorch Inference Benchmarking**, reporting average generation latency over datacenter configurations at 1, 4, and 8 GPUs. Diffusers values are from PBR `#309434`, **FP8 Cosmos3-Nano/Super Generator Diffusers Inference Benchmarking**, measured on a single GPU only and at 480p and 720p only, which is why the 256p column is empty for Diffusers and why its rows are empty wherever a block reports eight GPUs. Neither campaign covered H100 NVL or H200 NVL, so those GPUs are absent from this page. GB300 appears only in the Diffusers campaign. vLLM-Omni, TensorRT-LLM, and NIM have no FP8 results yet. Values are rounded to two decimal places.
+
+These reports establish the reported timing matrix but do not expose every prompt and action payload in this repository. The linked public recipes explain modality behavior and provide representative payloads; their example-specific frame counts and action chunk sizes should not be treated as the exact internal benchmark inputs.
+
+## Workload definitions
+
+| Workload | Input | Output |
+|---|---|---|
+| Text-to-image (`t2i`) | Text prompt | Generated image |
+| Text-to-video (`t2v`) | Text prompt | Generated video |
+| Image-to-video (`i2v`) | Text prompt and source image | Generated video |
+| Video-to-video (`v2v`) | Text prompt and source video | Generated video |
+| Text-to-audio-and-video (`t2av`) | Text prompt | Synchronized video and sound |
+| Video-to-audio-and-video (`v2av`) | Text prompt and source video | Generated video with synchronized sound |
+| Image-to-audio-and-video (`i2av`) | Text prompt and source image | Generated video with synchronized sound |
+| Transfer video-to-video (`transfer`) | Text prompt, source video, and one control hint | Generated video steered by that hint |
+| Forward dynamics | Initial visual observation and an action trajectory | Future-observation rollout video |
+| Inverse dynamics | Observed video | Recovered action trajectory; some serving integrations also return video |
+| Policy | Initial visual observation, instruction, and optional state | Predicted action trajectory and, for general Generator paths, a rollout video |
+
+The PBR uses `t2av`, `v2av`, and `i2av`; some public recipes call the same sound-producing modes `t2vs`, `v2vs`, and `i2vs`. See the [audiovisual cookbook](../cookbooks/cosmos3/generator/audiovisual/README.md) for generation inputs and the [action cookbook](../cookbooks/cosmos3/generator/action/README.md) for action representations and output contracts.
+
+## Primary vision generation
+
+### Text-to-Video (t2v)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 15.27 | 154.79 | 589.57 |
+| | Diffusers | 1 | | 386.15 | |
+| **H20** | PyTorch | 1 | 37.03 | 381.98 | 1505.14 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 9.15 | 83.30 | |
+| | Diffusers | 1 | | 234.65 | 830.32 |
+| **H200 141GB HBM3** | PyTorch | 1 | 9.00 | 85.98 | 322.54 |
+| | Diffusers | 1 | | 231.20 | 825.50 |
+| **B200** | PyTorch | 1 | 5.25 | 45.67 | 168.91 |
+| | Diffusers | 1 | | 130.78 | 405.87 |
+| **B300** | PyTorch | 1 | 4.92 | 42.14 | 149.55 |
+| | Diffusers | 1 | | 120.69 | 381.36 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 109.65 | 325.76 |
+
+### Image-to-Video (i2v)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 15.21 | 154.24 | 587.19 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 37.09 | 380.01 | 1501.45 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 8 | 5.75 | 19.08 | 55.33 |
+| | Diffusers | 8 | | | |
+| **H200 141GB HBM3** | PyTorch | 1 | 9.02 | 85.61 | 318.65 |
+| | Diffusers | 1 | | 234.20 | 819.74 |
+| **B200** | PyTorch | 1 | 5.18 | 45.24 | 167.93 |
+| | Diffusers | 1 | | 129.97 | 408.14 |
+| **B300** | PyTorch | 1 | 4.96 | 41.10 | 151.74 |
+| | Diffusers | 1 | | 120.90 | |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 108.89 | 327.89 |
+
+### Text-to-Image (t2i)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 1.75 | 2.76 | 5.13 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 2.33 | 5.73 | 12.01 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 1.84 | 1.92 | 2.94 |
+| | Diffusers | 1 | | 21.47 | 24.36 |
+| **H200 141GB HBM3** | PyTorch | 1 | 1.88 | 1.85 | 2.98 |
+| | Diffusers | 1 | | 19.90 | 23.20 |
+| **B200** | PyTorch | 1 | 1.48 | 1.47 | 1.85 |
+| | Diffusers | 1 | | 17.38 | 19.21 |
+| **B300** | PyTorch | 1 | 2.37 | 2.29 | 2.47 |
+| | Diffusers | 1 | | | 18.40 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 22.73 | 20.98 |
+
+Notes:
+1. All times measured on identical workloads (same seed, sampler settings, prompt).
+2. Multi-GPU configurations use tensor parallelism.
+3. Values are average generation latency in seconds; lower is better.
+4. The **GPUs** column gives the number of GPUs behind every value in that row, and is the same for every engine in a GPU block so the rows can be compared directly.
+5. Diffusers FP8 was measured on one GPU at 480p and 720p only.
+6. FP8 is faster than BF16 for the PyTorch path throughout. For the Diffusers path it only pays off on long video workloads: short ones are slower in FP8, `t2i` consistently so by roughly a factor of two, which suggests a fixed quantization overhead that the short runs cannot amortize. Compare against the BF16 page before choosing a precision for a short workload.
+
+## Additional audiovisual generation
+
+### Video-to-Video (v2v)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 14.60 | 159.65 | 611.60 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 35.78 | 396.97 | 1551.74 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 8 | 5.79 | 19.97 | 57.83 |
+| | Diffusers | 8 | | | |
+| **H200 141GB HBM3** | PyTorch | 1 | 8.74 | 89.08 | 334.16 |
+| | Diffusers | 1 | | 233.86 | 829.09 |
+| **B200** | PyTorch | 1 | 4.95 | 46.10 | 174.67 |
+| | Diffusers | 1 | | 132.66 | 410.66 |
+| **B300** | PyTorch | 1 | 4.74 | 43.03 | 157.26 |
+| | Diffusers | 1 | | 123.34 | 384.10 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 109.88 | 325.10 |
+
+### Text-to-Audio-and-Video (t2av)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 26.29 | 167.44 | 607.06 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 61.37 | 414.65 | 1539.41 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 8 | 6.27 | 20.73 | 58.41 |
+| | Diffusers | 8 | | | |
+| **H200 141GB HBM3** | PyTorch | 1 | 15.05 | 92.13 | 335.54 |
+| | Diffusers | 1 | | 237.46 | 821.20 |
+| **B200** | PyTorch | 1 | 8.82 | 49.69 | 173.99 |
+| | Diffusers | 1 | | 131.90 | 410.84 |
+| **B300** | PyTorch | 1 | 8.56 | 44.96 | 157.74 |
+| | Diffusers | 1 | | | 382.21 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 109.41 | 320.27 |
+
+### Video-to-Audio-and-Video (v2av)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | — | | | |
+| | Diffusers | — | | | |
+| **H20** | PyTorch | — | | | |
+| | Diffusers | — | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 240.63 | |
+| **H200 141GB HBM3** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 238.03 | 826.01 |
+| **B200** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 133.87 | 413.17 |
+| **B300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 123.61 | 386.33 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 110.98 | 334.54 |
+
+### Image-to-Audio-and-Video (i2av)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 25.77 | 165.51 | 602.27 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 59.59 | 408.98 | 1511.82 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 8 | 6.08 | 19.64 | 55.85 |
+| | Diffusers | 8 | | | |
+| **H200 141GB HBM3** | PyTorch | 1 | 14.59 | 90.77 | 330.04 |
+| | Diffusers | 1 | | 238.95 | 831.19 |
+| **B200** | PyTorch | 1 | 8.52 | 48.68 | 172.03 |
+| | Diffusers | 1 | | 132.97 | 418.44 |
+| **B300** | PyTorch | 1 | 8.30 | 44.71 | 155.68 |
+| | Diffusers | 1 | | 122.66 | 384.16 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 112.33 | 324.87 |
+
+## Transfer generation
+
+Transfer conditions a video-to-video generation on a structural control hint
+extracted from the source video. Each control is reported separately because
+the hint changes how much of the frame the model must synthesise.
+
+| GPU | Transfer control | Engine | GPUs | 256p | 480p | 720p |
+|---|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | blur | PyTorch | 1 | 56.31 | 348.18 | 1312.06 |
+| | | Diffusers | 1 | | | |
+| | depth | PyTorch | 1 | 53.67 | 360.23 | 1350.49 |
+| | | Diffusers | 1 | | | |
+| | edge | PyTorch | 1 | 45.73 | 347.50 | 1329.40 |
+| | | Diffusers | 1 | | | |
+| | multi_control | PyTorch | — | | | |
+| | | Diffusers | — | | | |
+| | seg | PyTorch | 1 | 49.86 | 367.16 | 1402.75 |
+| | | Diffusers | 1 | | | |
+| | wsm | PyTorch | 1 | 43.38 | 275.08 | 999.98 |
+| | | Diffusers | 1 | | | |
+| **H20** | blur | PyTorch | 1 | 132.90 | 857.75 | 3317.89 |
+| | | Diffusers | 1 | | | |
+| | depth | PyTorch | 1 | 125.40 | 888.61 | 3434.99 |
+| | | Diffusers | 1 | | | |
+| | edge | PyTorch | 1 | 107.20 | 867.13 | 3423.93 |
+| | | Diffusers | 1 | | | |
+| | multi_control | PyTorch | 1 | 129.52 | 1399.05 | 5934.07 |
+| | | Diffusers | 1 | | | |
+| | seg | PyTorch | 1 | 117.22 | 912.61 | 3473.61 |
+| | | Diffusers | 1 | | | |
+| | wsm | PyTorch | 1 | 100.62 | 677.55 | 2530.15 |
+| | | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | blur | PyTorch | 8 | 25.70 | 74.88 | 211.62 |
+| | | Diffusers | 8 | | | |
+| | depth | PyTorch | 8 | 24.13 | 76.10 | 219.20 |
+| | | Diffusers | 8 | | | |
+| | edge | PyTorch | 8 | 23.24 | 73.96 | 216.16 |
+| | | Diffusers | 8 | | | |
+| | multi_control | PyTorch | 8 | 26.52 | 110.00 | 380.70 |
+| | | Diffusers | 8 | | | |
+| | seg | PyTorch | 8 | 27.41 | 83.47 | 236.85 |
+| | | Diffusers | 8 | | | |
+| | wsm | PyTorch | 1 | 25.48 | 149.06 | |
+| | | Diffusers | 1 | | 289.78 | 923.57 |
+| **H200 141GB HBM3** | blur | PyTorch | 1 | 32.51 | 192.22 | 727.48 |
+| | | Diffusers | 1 | | 603.23 | 2115.64 |
+| | depth | PyTorch | 1 | 30.58 | 200.84 | 741.97 |
+| | | Diffusers | 1 | | 621.13 | 2137.67 |
+| | edge | PyTorch | 1 | 26.71 | 195.05 | 730.81 |
+| | | Diffusers | 1 | | 598.72 | 2100.45 |
+| | multi_control | PyTorch | 1 | 31.90 | 316.92 | 1289.45 |
+| | | Diffusers | 1 | | | |
+| | seg | PyTorch | 1 | 29.32 | 204.51 | 736.27 |
+| | | Diffusers | 1 | | 602.62 | 2122.42 |
+| | wsm | PyTorch | 1 | 25.08 | 155.47 | 542.31 |
+| | | Diffusers | 1 | | 285.48 | 923.68 |
+| **B200** | blur | PyTorch | 1 | 19.26 | 103.45 | 374.36 |
+| | | Diffusers | 1 | | 326.36 | 1025.97 |
+| | depth | PyTorch | 1 | 18.14 | 107.49 | 385.52 |
+| | | Diffusers | 1 | | 334.83 | 1044.04 |
+| | edge | PyTorch | 1 | 15.76 | 103.47 | 374.81 |
+| | | Diffusers | 1 | | 327.94 | 1029.37 |
+| | multi_control | PyTorch | — | | | |
+| | | Diffusers | — | | | |
+| | seg | PyTorch | 1 | 17.60 | 109.95 | 400.23 |
+| | | Diffusers | 1 | | 326.72 | 1029.82 |
+| | wsm | PyTorch | 1 | 15.36 | 82.54 | 285.69 |
+| | | Diffusers | 1 | | 161.39 | 469.48 |
+| **B300** | blur | PyTorch | 1 | 18.27 | 94.98 | 331.00 |
+| | | Diffusers | 1 | | 301.73 | 956.39 |
+| | depth | PyTorch | 1 | 17.29 | 100.31 | 342.30 |
+| | | Diffusers | 1 | | 315.60 | 974.65 |
+| | edge | PyTorch | 1 | 15.61 | 95.30 | 343.94 |
+| | | Diffusers | 1 | | 303.64 | 956.04 |
+| | multi_control | PyTorch | — | | | |
+| | | Diffusers | — | | | |
+| | seg | PyTorch | 1 | 18.14 | 102.72 | 358.43 |
+| | | Diffusers | 1 | | 304.87 | 961.79 |
+| | wsm | PyTorch | 1 | 15.66 | 76.04 | 258.05 |
+| | | Diffusers | 1 | | 150.02 | 430.41 |
+| **GB300** | blur | PyTorch | 1 | | | |
+| | | Diffusers | 1 | | 268.46 | 806.60 |
+| | depth | PyTorch | 1 | | | |
+| | | Diffusers | 1 | | 271.61 | 822.16 |
+| | edge | PyTorch | 1 | | | |
+| | | Diffusers | 1 | | 260.92 | 811.23 |
+| | multi_control | PyTorch | — | | | |
+| | | Diffusers | — | | | |
+| | seg | PyTorch | 1 | | | |
+| | | Diffusers | 1 | | 268.54 | 804.36 |
+| | wsm | PyTorch | 1 | | | |
+| | | Diffusers | 1 | | 134.03 | 365.92 |
+
+Transfer notes:
+1. Control hints follow the `extra_params` names: `blur`, `depth`, `edge`, `multi_control`, `seg`, and `wsm`. `multi_control` combines several hints in one request.
+2. The PyTorch campaign reports `segmentation`, which is the same control as `seg` in the Diffusers campaign.
+3. Diffusers FP8 has no `multi_control` measurements.
+
+## Action generation
+
+### Forward Dynamics — Autonomous Vehicle (AV)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 16.71 | 16.73 | 16.72 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 40.31 | 40.29 | 40.28 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 9.82 | 9.80 | 9.83 |
+| | Diffusers | 1 | | 33.43 | 33.83 |
+| **H200 141GB HBM3** | PyTorch | 1 | 9.48 | 9.63 | 9.48 |
+| | Diffusers | 1 | | 32.07 | 32.65 |
+| **B200** | PyTorch | 1 | 5.42 | 5.43 | 5.42 |
+| | Diffusers | 1 | | 21.96 | 22.05 |
+| **B300** | PyTorch | 1 | 5.07 | 5.06 | 5.19 |
+| | Diffusers | 1 | | | 21.84 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 19.76 | 20.41 |
+
+### Forward Dynamics — Camera
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 15.77 | 15.75 | 15.78 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 38.35 | 37.96 | 37.97 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 9.25 | 9.28 | 9.25 |
+| | Diffusers | 1 | | | |
+| **H200 141GB HBM3** | PyTorch | 1 | 8.99 | 8.99 | 8.99 |
+| | Diffusers | 1 | | | |
+| **B200** | PyTorch | 1 | 5.14 | 5.15 | 5.12 |
+| | Diffusers | 1 | | | |
+| **B300** | PyTorch | 1 | 4.82 | 4.86 | 4.80 |
+| | Diffusers | 1 | | | |
+
+### Forward Dynamics — Robot
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 3.58 | 3.58 | 3.58 |
+| | Diffusers | 1 | | 17.42 | |
+| **H20** | PyTorch | 1 | 8.49 | 8.50 | 8.50 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 2.14 | 2.14 | 2.14 |
+| | Diffusers | 1 | | 13.90 | 14.04 |
+| **H200 141GB HBM3** | PyTorch | 1 | 2.09 | 2.10 | 2.10 |
+| | Diffusers | 1 | | 13.20 | 13.35 |
+| **B200** | PyTorch | 1 | 1.27 | 1.26 | 1.28 |
+| | Diffusers | 1 | | 10.60 | 10.71 |
+| **B300** | PyTorch | 1 | 1.30 | 1.32 | 1.31 |
+| | Diffusers | 1 | | 10.24 | 11.15 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 10.71 | 12.12 |
+
+### Inverse Dynamics — Autonomous Vehicle (AV)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 28.37 | 28.36 | 28.29 |
+| | Diffusers | 1 | | | 51.58 |
+| **H20** | PyTorch | 1 | 68.74 | 68.70 | 68.72 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 16.56 | 16.51 | 16.51 |
+| | Diffusers | 1 | | 33.15 | 33.73 |
+| **H200 141GB HBM3** | PyTorch | 1 | 15.96 | 15.97 | 15.95 |
+| | Diffusers | 1 | | 31.93 | 32.37 |
+| **B200** | PyTorch | 1 | 9.01 | 9.03 | 9.02 |
+| | Diffusers | 1 | | 21.73 | 21.84 |
+| **B300** | PyTorch | 1 | 8.51 | 8.49 | 8.51 |
+| | Diffusers | 1 | | 20.85 | 20.99 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 19.50 | 20.02 |
+
+### Inverse Dynamics — Robot
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 5.72 | 5.72 | 5.73 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 13.84 | 13.73 | 13.71 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 3.39 | 3.39 | 3.39 |
+| | Diffusers | 1 | | 13.91 | 14.02 |
+| **H200 141GB HBM3** | PyTorch | 1 | 3.37 | 3.32 | 3.32 |
+| | Diffusers | 1 | | 13.10 | 13.38 |
+| **B200** | PyTorch | 1 | 1.97 | 1.97 | 1.96 |
+| | Diffusers | 1 | | 10.57 | 10.70 |
+| **B300** | PyTorch | 1 | 1.95 | 1.90 | 1.97 |
+| | Diffusers | 1 | | 10.95 | 11.30 |
+| **GB300** | PyTorch | 1 | | | |
+| | Diffusers | 1 | | 12.74 | 13.76 |
+
+### Policy — Autonomous Vehicle (AV)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 16.74 | 16.75 | 16.73 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 40.58 | 40.29 | 40.59 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 9.80 | 9.83 | 9.81 |
+| | Diffusers | 1 | | | |
+| **H200 141GB HBM3** | PyTorch | 1 | 9.62 | 9.61 | 9.62 |
+| | Diffusers | 1 | | | |
+| **B200** | PyTorch | 1 | 5.42 | 5.33 | 5.40 |
+| | Diffusers | 1 | | | |
+| **B300** | PyTorch | 1 | 5.20 | 5.18 | 5.20 |
+| | Diffusers | 1 | | | |
+
+### Policy — Robot
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 1 | 3.42 | 3.41 | 3.42 |
+| | Diffusers | 1 | | | |
+| **H20** | PyTorch | 1 | 8.17 | 8.11 | 8.10 |
+| | Diffusers | 1 | | | |
+| **H100 80GB HBM3** | PyTorch | 1 | 2.05 | 2.05 | 2.04 |
+| | Diffusers | 1 | | | |
+| **H200 141GB HBM3** | PyTorch | 1 | 2.04 | 2.00 | 2.04 |
+| | Diffusers | 1 | | | |
+| **B200** | PyTorch | 1 | 1.23 | 1.21 | 1.24 |
+| | Diffusers | 1 | | | |
+| **B300** | PyTorch | 1 | 1.19 | 1.18 | 1.18 |
+| | Diffusers | 1 | | | |
+
+Action and additional-modality notes:
+1. Forward-dynamics cells for the AV domain are the mean of the forward, left, and right trajectories; inverse-dynamics cells are the mean of the two inverse trajectories.
+2. The Diffusers FP8 campaign covers forward and inverse dynamics for the AV and Robot domains only, so the Camera and Policy rows carry PyTorch values alone.
+3. Policy-DROID is a separate checkpoint and was not part of either FP8 campaign.
diff --git a/inference_benchmarks/cosmos3-super-generator.md b/inference_benchmarks/cosmos3-super-generator.md
new file mode 100644
index 00000000..c96c7490
--- /dev/null
+++ b/inference_benchmarks/cosmos3-super-generator.md
@@ -0,0 +1,921 @@
+# Cosmos3-Super Generator Inference Benchmarks
+
+[Back to the inference benchmark index](../inference_benchmarks.md)
+
+These tables report **Cosmos3-Super Generator** latency in seconds. Lower is better.
+
+Every row reports one GPU configuration, named in the **GPUs** column, and all three resolutions in that row come from it. The configuration is one GPU when the model fits on a single device at its highest resolution, 720p, and eight GPUs when it does not. Within one GPU's block every engine reports the same configuration, so a column can be read straight across the runtimes. Cosmos3-Super is reported at one GPU on H200 NVL, H200 141GB HBM3, B200, and B300, and at eight GPUs on RTX PRO 6000 Blackwell, H20, H100 NVL, and H100 80GB HBM3. vLLM-Omni does fit on a single GPU on those four smaller-memory parts, but is reported at eight alongside the other runtimes; PyTorch is the engine that sets the eight-GPU configuration on the H200 parts. Because the configuration varies between rows, read the **GPUs** column before comparing latencies down a column.
+
+Empty cells mean that a run has not been completed for that GPU, engine, or resolution; they do not indicate that a combination is unsupported.
+
+## Table of Contents
+
+- [Benchmark methodology](#benchmark-methodology)
+- [Workload definitions](#workload-definitions)
+- [Primary vision generation](#primary-vision-generation)
+ - [Text-to-Video (t2v)](#text-to-video-t2v)
+ - [Image-to-Video (i2v)](#image-to-video-i2v)
+ - [Text-to-Image (t2i)](#text-to-image-t2i)
+- [Additional audiovisual generation](#additional-audiovisual-generation)
+ - [Video-to-Video (v2v)](#video-to-video-v2v)
+ - [Text-to-Audio-and-Video (t2av)](#text-to-audio-and-video-t2av)
+ - [Video-to-Audio-and-Video (v2av)](#video-to-audio-and-video-v2av)
+ - [Image-to-Audio-and-Video (i2av)](#image-to-audio-and-video-i2av)
+- [Transfer generation](#transfer-generation)
+- [Action generation](#action-generation)
+ - [Forward Dynamics — AV](#forward-dynamics--autonomous-vehicle-av)
+ - [Forward Dynamics — Camera](#forward-dynamics--camera)
+ - [Forward Dynamics — Robot](#forward-dynamics--robot)
+ - [Inverse Dynamics — AV](#inverse-dynamics--autonomous-vehicle-av)
+ - [Inverse Dynamics — Robot](#inverse-dynamics--robot)
+ - [Policy — AV](#policy--autonomous-vehicle-av)
+ - [Policy — Robot](#policy--robot)
+ - [Policy — DROID](#policy--droid)
+
+## Benchmark methodology
+
+The primary t2v, i2v, and t2i tables cover PyTorch, vLLM-Omni, Diffusers, TensorRT-LLM, and NIM. Their vLLM-Omni values are from PBR `#307999`, **Cosmos3-Generator vLLM-Omni Inference Benchmarking (t2i, t2v, i2v)**; the PyTorch and NIM values preserve the previously published campaigns. Those tables use BF16 precision, batch size 1, and matched prompts, seeds, and sampler settings where documented. Video workloads follow the standard Cosmos3 generation profile of 189 frames at 24 FPS unless a resolution tier limits frame count.
+
+The additional audiovisual and action tables come from three internal benchmark reports. PyTorch values are from PBR `#308197`, **Cosmos3-Generator OSS Inference Benchmarking 32B and 8B (189 frames)**: average generation (sampling) latency from the native OSS path, using **CUDA Graphs disabled** and the **latency** automatic-sharding preset. vLLM-Omni values for text-to-audio-and-video (`t2av`/`t2vs`) and image-to-audio-and-video (`i2av`/`i2vs`) are from PBR `#308195`. vLLM-Omni action values are from PBR `#308481`, **Cosmos3-Generator vLLM-Omni Inference Benchmarking (action)**, measured with the `vllm/vllm-omni:cosmos3` image and the official action cookbook samples; `DIFFUSION_ATTENTION_BACKEND=TORCH_SDPA` was not set. Forward-dynamics cells are the mean of `av_forward`, `av_left`, and `av_right`; inverse-dynamics cells are the mean of `av_inverse_0` and `av_inverse_1`. That action sweep covers 1, 2, and 4 GPUs only, because its 8-GPU Ulysses runs failed a sequence-length divisibility check; those rows therefore report the single-GPU configuration. Policy-DROID is a separate checkpoint and was measured only at 480p on one GPU. That action sweep did not cover Super on H20, H100 NVL, or H100 80GB HBM3. Diffusers values come from four further reports: PBR `#308202` (all modalities) and PBR `#308451` (video-to-video) on one GPU, PBR `#308918` for 4- and 8-GPU runs, and PBR `#308587` for transfer. vLLM-Omni transfer values are from PBR `#308574`. Where PBR `#308918` offers several tensor- and context-parallel splits at the same GPU count, the fastest is published. Its 1-GPU numbers are not used, because that sweep ran a different denoising-step budget than the single-GPU reports. TensorRT-LLM values are from PBR `#308000`, **Cosmos3-Generator TRT-LLM Inference Benchmarking**, which sweeps tensor-parallel, CFG-parallel, and Ulysses-parallel splits at each GPU count; the fastest split at the count a row reports is the one published. That campaign covers six GPUs, so the TensorRT-LLM rows for H100 NVL and H200 NVL are empty, and it includes no action workloads. Values are rounded to two decimal places.
+
+These reports establish the reported timing matrix but do not expose every prompt and action payload in this repository. The linked public recipes explain modality behavior and provide representative payloads; their example-specific frame counts and action chunk sizes should not be treated as the exact internal benchmark inputs.
+
+## Workload definitions
+
+| Workload | Input | Output |
+|---|---|---|
+| Video-to-video (`v2v`) | Text prompt and source video | Generated video |
+| Text-to-audio-and-video (`t2av`) | Text prompt | Synchronized video and sound |
+| Video-to-audio-and-video (`v2av`) | Text prompt and source video | Generated video with synchronized sound |
+| Image-to-audio-and-video (`i2av`) | Text prompt and source image | Generated video with synchronized sound |
+| Transfer video-to-video (`transfer`) | Text prompt, source video, and one control hint | Generated video steered by that hint |
+| Forward dynamics | Initial visual observation and an action trajectory | Future-observation rollout video |
+| Inverse dynamics | Observed video | Recovered action trajectory; some serving integrations also return video |
+| Policy | Initial visual observation, instruction, and optional state | Predicted action trajectory and, for general Generator paths, a rollout video |
+| Policy-DROID | Multiview wrist/exterior observations for the DROID embodiment | Predicted action chunk from the Policy-DROID checkpoint |
+
+The PBR uses `t2av`, `v2av`, and `i2av`; some public recipes call the same sound-producing modes `t2vs`, `v2vs`, and `i2vs`. See the [audiovisual cookbook](../cookbooks/cosmos3/generator/audiovisual/README.md) for generation inputs and the [action cookbook](../cookbooks/cosmos3/generator/action/README.md) for action representations and output contracts. vLLM-Omni request shapes are maintained in the [Super recipe](https://github.com/vllm-project/vllm-omni/blob/main/recipes/cosmos3/Cosmos3-Super.md). Public recipes cover more embodiments than this PBR; the action tables below intentionally use only its measured domain rows.
+
+## Primary vision generation
+
+### Text-to-Video (t2v)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 8 | 66.04 | 118.90 | 427.16 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 25.39 | 154.25 | 437.57 |
+| | TensorRT-LLM | 8 | 0.21 | 0.13 | 0.10 |
+| | NIM | 8 | 13.99 | 99.05 | 286.02 |
+| **H20** | PyTorch | 8 | 27.72 | 152.46 | 492.41 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 26.66 | 161.49 | 517.37 |
+| | TensorRT-LLM | 8 | 0.06 | 0.01 | 0.01 |
+| | NIM | 8 | 12.95 | 110.71 | 395.56 |
+| **H100 NVL** | PyTorch | 8 | 16.83 | 64.14 | 186.19 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 24.21 | 108.70 | 322.28 |
+| | TensorRT-LLM | — | | | |
+| | NIM | 8 | 12.73 | 66.07 | 197.32 |
+| **H200 NVL** | PyTorch | 8 | 24.78 | 47.69 | 142.35 |
+| | vLLM-Omni | 1 | 27.54 | 252.33 | 911.49 |
+| | Diffusers | 1 | 33.00 | 286.80 | 1036.00 |
+| | TensorRT-LLM | — | | | |
+| | NIM | 1 | 17.13 | 200.00 | 811.41 |
+| **H100 80GB HBM3** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 19.40 | 56.39 | 174.57 |
+| | TensorRT-LLM | 8 | 0.04 | 0.02 | 0.04 |
+| | NIM | 8 | 5.89 | 35.52 | 114.92 |
+| **H200 141GB HBM3** | PyTorch | 8 | 11.82 | 41.78 | 123.49 |
+| | vLLM-Omni | 1 | 25.61 | 219.11 | 769.63 |
+| | Diffusers | 1 | 31.00 | 251.60 | 886.20 |
+| | TensorRT-LLM | 1 | 24.21 | 234.08 | 853.44 |
+| | NIM | 1 | 15.95 | 174.71 | 695.89 |
+| **B200** | PyTorch | 1 | 14.66 | 114.38 | 407.50 |
+| | vLLM-Omni | 1 | 13.84 | 114.08 | 383.84 |
+| | Diffusers | 1 | 19.00 | 127.20 | 414.40 |
+| | TensorRT-LLM | 1 | 12.32 | 104.63 | 367.12 |
+| | NIM | 1 | 9.09 | 82.39 | 314.68 |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | 14.57 | 109.03 | 366.66 |
+| | Diffusers | 1 | 17.73 | 125.70 | 398.94 |
+| | TensorRT-LLM | 1 | 11.85 | 97.66 | 333.28 |
+| | NIM | 1 | 9.67 | 79.73 | 292.35 |
+
+### Image-to-Video (i2v)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 8 | 66.54 | 118.95 | 427.96 |
+| | vLLM-Omni | 8 | 11.66 | 80.94 | 240.27 |
+| | Diffusers | 8 | 26.29 | 156.16 | 540.65 |
+| | TensorRT-LLM | 8 | 0.19 | 0.13 | 0.09 |
+| | NIM | 8 | 14.48 | 100.23 | 289.93 |
+| **H20** | PyTorch | 8 | 28.22 | 153.19 | 491.93 |
+| | vLLM-Omni | 8 | 19.65 | 148.77 | 488.51 |
+| | Diffusers | 8 | 27.65 | 165.91 | 530.44 |
+| | TensorRT-LLM | 8 | 0.06 | 0.01 | 0.01 |
+| | NIM | 8 | 14.06 | 114.49 | 405.68 |
+| **H100 NVL** | PyTorch | 8 | 16.96 | 64.17 | 186.47 |
+| | vLLM-Omni | 8 | 8.48 | 59.44 | 212.53 |
+| | Diffusers | 8 | 25.45 | 112.36 | 325.56 |
+| | TensorRT-LLM | — | | | |
+| | NIM | 8 | 13.30 | 67.34 | 201.39 |
+| **H200 NVL** | PyTorch | 8 | 24.70 | 47.60 | 141.62 |
+| | vLLM-Omni | 1 | 27.90 | 254.29 | 915.05 |
+| | Diffusers | 1 | 33.00 | 287.20 | 1034.60 |
+| | TensorRT-LLM | — | | | |
+| | NIM | 1 | 17.51 | 201.45 | 817.35 |
+| **H100 80GB HBM3** | PyTorch | — | | | |
+| | vLLM-Omni | 8 | 6.48 | 38.31 | |
+| | Diffusers | 8 | 19.98 | 55.63 | 184.81 |
+| | TensorRT-LLM | 8 | 0.03 | 0.03 | 0.04 |
+| | NIM | 8 | 6.49 | 36.81 | 118.77 |
+| **H200 141GB HBM3** | PyTorch | 8 | 11.80 | 42.10 | 123.57 |
+| | vLLM-Omni | 1 | 25.47 | 220.70 | 766.33 |
+| | Diffusers | 1 | 31.00 | 249.20 | 879.20 |
+| | TensorRT-LLM | 1 | 24.46 | 230.02 | |
+| | NIM | 1 | 16.39 | 175.95 | 699.13 |
+| **B200** | PyTorch | 1 | 14.71 | 112.40 | 397.31 |
+| | vLLM-Omni | 1 | 14.13 | 115.17 | 386.35 |
+| | Diffusers | 1 | 19.20 | 127.00 | 414.80 |
+| | TensorRT-LLM | 1 | 12.67 | 105.74 | 372.60 |
+| | NIM | 1 | 9.36 | 83.19 | 316.76 |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | 14.14 | 111.42 | 368.73 |
+| | Diffusers | 1 | 25.21 | 132.23 | 410.81 |
+| | TensorRT-LLM | 1 | 12.15 | 98.90 | 336.20 |
+| | NIM | 1 | 9.73 | 80.51 | 294.11 |
+
+### Text-to-Image (t2i)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 8 | 93.18 | 93.39 | 93.47 |
+| | vLLM-Omni | 8 | 3.11 | 3.54 | 5.70 |
+| | Diffusers | 8 | 16.90 | 17.52 | 16.73 |
+| | TensorRT-LLM | 8 | 0.09 | 0.09 | -0.04 |
+| **H20** | PyTorch | 8 | 14.18 | 16.46 | 20.92 |
+| | vLLM-Omni | 8 | 5.12 | 5.44 | 8.85 |
+| | Diffusers | 8 | 18.29 | 18.48 | 18.46 |
+| | TensorRT-LLM | 8 | 0.02 | 0.13 | 0.03 |
+| **H100 NVL** | PyTorch | 8 | 19.86 | 19.80 | 19.87 |
+| | vLLM-Omni | 8 | 3.54 | 3.48 | 4.11 |
+| | Diffusers | 8 | 16.56 | 16.60 | 16.88 |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 8 | 32.86 | 33.05 | 33.16 |
+| | vLLM-Omni | 1 | 2.73 | 6.28 | 11.02 |
+| | Diffusers | 1 | 5.00 | 8.00 | 12.00 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | — | | | |
+| | vLLM-Omni | 8 | 5.09 | 5.16 | 4.91 |
+| | Diffusers | 8 | 17.97 | 18.03 | 19.28 |
+| | TensorRT-LLM | 8 | 0.06 | 0.02 | 0.02 |
+| **H200 141GB HBM3** | PyTorch | 8 | 13.48 | 13.53 | 13.50 |
+| | vLLM-Omni | 1 | 2.83 | 5.70 | 10.24 |
+| | Diffusers | 1 | 5.00 | 8.00 | 11.00 |
+| | TensorRT-LLM | 1 | 2.24 | 5.10 | 10.77 |
+| **B200** | PyTorch | 1 | 4.51 | 4.78 | 7.25 |
+| | vLLM-Omni | 1 | 2.32 | 3.29 | 5.99 |
+| | Diffusers | 1 | 4.40 | 6.00 | 8.00 |
+| | TensorRT-LLM | 1 | 1.69 | 2.84 | 5.72 |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | 5.05 | 3.79 | 7.08 |
+| | Diffusers | 1 | 6.49 | 6.76 | 7.11 |
+| | TensorRT-LLM | 1 | 2.40 | 2.77 | 5.43 |
+
+Notes:
+1. All times measured on identical workloads (same seed, sampler settings, prompt).
+2. Multi-GPU configurations use tensor parallelism, except TensorRT-LLM, which may also split across CFG and Ulysses dimensions.
+3. vLLM-Omni numbers are for the upcoming public release in the vLLM-Omni repo and are subject to change before GA.
+4. Diffusers numbers use the HuggingFace `diffusers` integration without custom CUDA graphs. Single-GPU values come from PBR `#308202` and PBR `#308451`; multi-GPU values from PBR `#308918`.
+5. At 256p, multi-GPU configurations on B300 may underperform single-GPU because of small-workload tensor-parallel overhead, so single-GPU is the recommended deployment at this resolution.
+6. PyTorch numbers report average generation (sampling) time from OSS inference benchmarking.
+7. NIM numbers use latency profiles with FP8 precision and report end-to-end `Request Latency s`, including request processing, video generation, output encoding, and returning the response.
+8. The 720p i2v cell for vLLM-Omni on H100 80GB HBM3 is empty because the multi-GPU runs for it returned times far below the 480p result, which is not physically plausible; the measurement is being rerun.
+
+## Additional audiovisual generation
+
+### Video-to-Video (v2v)
+
+A text prompt and source video condition a generated continuation or transformation.
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 8 | 66.31 | 118.92 | 427.19 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 28.39 | 158.14 | 545.45 |
+| | TensorRT-LLM | 8 | 0.21 | 0.13 | 0.10 |
+| **H20** | PyTorch | 8 | 27.98 | 153.02 | 491.75 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 28.18 | 167.95 | 532.68 |
+| | TensorRT-LLM | 8 | 0.06 | 0.02 | 0.01 |
+| **H100 NVL** | PyTorch | 8 | 16.79 | 63.84 | 183.64 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 25.01 | 112.47 | 348.31 |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 8 | 24.74 | 47.60 | 142.23 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 40.73 | 316.00 | 1093.16 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 21.61 | 57.74 | 188.43 |
+| | TensorRT-LLM | 8 | 0.01 | 0.03 | 0.03 |
+| **H200 141GB HBM3** | PyTorch | 8 | 11.76 | 41.85 | 123.09 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 41.17 | 269.44 | 916.41 |
+| | TensorRT-LLM | 1 | 24.19 | 230.98 | |
+| **B200** | PyTorch | 1 | 14.30 | 111.49 | 395.97 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 26.30 | 142.61 | 437.27 |
+| | TensorRT-LLM | 1 | 12.50 | 104.79 | 370.21 |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 25.86 | 139.04 | 416.98 |
+| | TensorRT-LLM | 1 | 11.95 | 97.75 | 333.72 |
+
+### Text-to-Audio-and-Video (t2av)
+
+A text prompt produces synchronized video and sound.
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 8 | 65.79 | 118.87 | 429.78 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | 8 | 0.21 | 0.13 | 0.10 |
+| **H20** | PyTorch | 8 | 27.73 | 152.53 | 492.38 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | 8 | 0.05 | 0.01 | 0.01 |
+| **H100 NVL** | PyTorch | 8 | 16.86 | 64.17 | 183.81 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 8 | 24.79 | 47.67 | 142.06 |
+| | vLLM-Omni | 1 | 29.07 | 260.51 | 916.51 |
+| | Diffusers | 1 | 35.00 | 291.40 | 1034.20 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | 8 | 11.74 | 41.49 | 123.35 |
+| | vLLM-Omni | 1 | 27.21 | 221.67 | 763.74 |
+| | Diffusers | 1 | 33.00 | 253.40 | 874.60 |
+| | TensorRT-LLM | 1 | 25.89 | 229.12 | |
+| **B200** | PyTorch | 1 | 14.52 | 112.99 | 395.20 |
+| | vLLM-Omni | 1 | 14.77 | 115.26 | 388.51 |
+| | Diffusers | 1 | 20.00 | 128.00 | 422.00 |
+| | TensorRT-LLM | 1 | 13.37 | 105.39 | 371.64 |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | 15.26 | 113.34 | 372.74 |
+| | Diffusers | 1 | 18.94 | 126.86 | 402.37 |
+| | TensorRT-LLM | 1 | 12.76 | 98.59 | 335.38 |
+
+### Video-to-Audio-and-Video (v2av)
+
+A text prompt and source video produce transformed video with synchronized sound.
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 8 | 66.10 | 118.88 | 428.64 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H20** | PyTorch | 8 | 28.00 | 152.78 | 492.63 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H100 NVL** | PyTorch | 8 | 16.79 | 64.69 | 183.62 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 8 | 24.73 | 47.67 | 143.06 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 48.42 | 320.70 | 1093.26 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | 8 | 11.74 | 41.59 | 123.06 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 43.23 | 270.19 | 909.99 |
+| | TensorRT-LLM | — | | | |
+| **B200** | PyTorch | 1 | 14.28 | 111.84 | 406.66 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 30.26 | 141.75 | 446.20 |
+| | TensorRT-LLM | — | | | |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 30.36 | 138.17 | 420.63 |
+| | TensorRT-LLM | — | | | |
+
+### Image-to-Audio-and-Video (i2av)
+
+A text prompt and source image produce video with synchronized sound.
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 8 | 66.27 | 119.05 | 429.26 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | 8 | 0.18 | 0.13 | 0.10 |
+| **H20** | PyTorch | 8 | 28.11 | 153.33 | 493.51 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | 8 | 0.05 | 0.01 | 0.01 |
+| **H100 NVL** | PyTorch | 8 | 16.85 | 64.19 | 186.66 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 8 | 24.69 | 47.65 | 142.18 |
+| | vLLM-Omni | 1 | 29.42 | 262.20 | 922.18 |
+| | Diffusers | 1 | 35.00 | 292.20 | 1037.00 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | 8 | 11.82 | 41.95 | 123.42 |
+| | vLLM-Omni | 1 | 27.58 | 220.57 | 774.15 |
+| | Diffusers | 1 | 33.00 | 256.00 | 880.40 |
+| | TensorRT-LLM | 1 | 26.41 | 233.74 | |
+| **B200** | PyTorch | 1 | 14.84 | 113.32 | 407.30 |
+| | vLLM-Omni | 1 | 15.15 | 116.54 | 396.11 |
+| | Diffusers | 1 | 20.00 | 128.00 | 423.00 |
+| | TensorRT-LLM | 1 | 13.65 | 106.62 | 374.24 |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | 16.46 | 114.02 | 373.17 |
+| | Diffusers | 1 | 29.16 | 134.46 | 414.22 |
+| | TensorRT-LLM | 1 | 13.25 | 99.94 | 338.12 |
+
+## Transfer generation
+
+Transfer conditions a video-to-video generation on a structural control hint
+extracted from the source video. Each control is reported separately because
+the hint changes how much of the frame the model must synthesise.
+
+| GPU | Transfer control | Engine | GPUs | 256p | 480p | 720p |
+|---|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | blur | PyTorch | 4 | | | |
+| | | vLLM-Omni | 4 | | | |
+| | | Diffusers | 4 | | | |
+| | | TensorRT-LLM | 4 | -0.19 | -0.28 | -0.37 |
+| | | NIM | 4 | | | |
+| | depth | PyTorch | 4 | | | |
+| | | vLLM-Omni | 4 | | | |
+| | | Diffusers | 4 | | | |
+| | | TensorRT-LLM | 4 | -0.19 | -0.28 | -0.37 |
+| | | NIM | 4 | | | |
+| | edge | PyTorch | 4 | | | |
+| | | vLLM-Omni | 4 | | | |
+| | | Diffusers | 4 | | | |
+| | | TensorRT-LLM | 4 | -0.19 | -0.28 | -0.37 |
+| | | NIM | 4 | | | |
+| | multi_control | PyTorch | 4 | | | |
+| | | vLLM-Omni | 4 | | | |
+| | | Diffusers | 4 | | | |
+| | | TensorRT-LLM | 4 | -0.19 | -0.32 | -0.40 |
+| | | NIM | 4 | | | |
+| | seg | PyTorch | 4 | | | |
+| | | vLLM-Omni | 4 | | | |
+| | | Diffusers | 4 | | | |
+| | | TensorRT-LLM | 4 | -0.19 | -0.28 | -0.37 |
+| | | NIM | 4 | | | |
+| | wsm | PyTorch | 4 | | | |
+| | | vLLM-Omni | 4 | | | |
+| | | Diffusers | 4 | | | |
+| | | TensorRT-LLM | 4 | -0.15 | -0.27 | -0.34 |
+| | | NIM | 4 | | | |
+| **H20** | blur | PyTorch | 4 | | | |
+| | | vLLM-Omni | 4 | | | |
+| | | Diffusers | 4 | | | |
+| | | TensorRT-LLM | 4 | -0.46 | -0.49 | -0.49 |
+| | | NIM | 4 | | | |
+| | depth | PyTorch | 4 | | | |
+| | | vLLM-Omni | 4 | | | |
+| | | Diffusers | 4 | | | |
+| | | TensorRT-LLM | 4 | -0.46 | -0.49 | -0.49 |
+| | | NIM | 4 | | | |
+| | edge | PyTorch | 4 | | | |
+| | | vLLM-Omni | 4 | | | |
+| | | Diffusers | 4 | | | |
+| | | TensorRT-LLM | 4 | -0.46 | -0.49 | -0.49 |
+| | | NIM | 4 | | | |
+| | multi_control | PyTorch | 4 | | | |
+| | | vLLM-Omni | 4 | | | |
+| | | Diffusers | 4 | | | |
+| | | TensorRT-LLM | 4 | -0.47 | -0.49 | -0.50 |
+| | | NIM | 4 | | | |
+| | seg | PyTorch | 4 | | | |
+| | | vLLM-Omni | 4 | | | |
+| | | Diffusers | 4 | | | |
+| | | TensorRT-LLM | 4 | -0.46 | 633.73 | -0.49 |
+| | | NIM | 4 | | | |
+| | wsm | PyTorch | 4 | | | |
+| | | vLLM-Omni | 4 | | | |
+| | | Diffusers | 4 | | | |
+| | | TensorRT-LLM | 4 | -0.46 | -0.48 | -0.49 |
+| | | NIM | 4 | | | |
+| **H100 NVL** | blur | PyTorch | — | | | |
+| | | vLLM-Omni | — | | | |
+| | | Diffusers | — | | | |
+| | | TensorRT-LLM | — | | | |
+| | | NIM | — | | | |
+| | depth | PyTorch | — | | | |
+| | | vLLM-Omni | — | | | |
+| | | Diffusers | — | | | |
+| | | TensorRT-LLM | — | | | |
+| | | NIM | — | | | |
+| | edge | PyTorch | — | | | |
+| | | vLLM-Omni | — | | | |
+| | | Diffusers | — | | | |
+| | | TensorRT-LLM | — | | | |
+| | | NIM | — | | | |
+| | multi_control | PyTorch | — | | | |
+| | | vLLM-Omni | — | | | |
+| | | Diffusers | — | | | |
+| | | TensorRT-LLM | — | | | |
+| | | NIM | — | | | |
+| | seg | PyTorch | — | | | |
+| | | vLLM-Omni | — | | | |
+| | | Diffusers | — | | | |
+| | | TensorRT-LLM | — | | | |
+| | | NIM | — | | | |
+| | wsm | PyTorch | — | | | |
+| | | vLLM-Omni | — | | | |
+| | | Diffusers | — | | | |
+| | | TensorRT-LLM | — | | | |
+| | | NIM | — | | | |
+| **H100 80GB HBM3** | blur | PyTorch | 4 | | | |
+| | | vLLM-Omni | 4 | | | |
+| | | Diffusers | 4 | | | |
+| | | TensorRT-LLM | 4 | 23.08 | 169.42 | 604.47 |
+| | | NIM | 4 | | | |
+| | depth | PyTorch | 4 | | | |
+| | | vLLM-Omni | 4 | | | |
+| | | Diffusers | 4 | | | |
+| | | TensorRT-LLM | 4 | 23.27 | 173.32 | 611.69 |
+| | | NIM | 4 | | | |
+| | edge | PyTorch | 4 | | | |
+| | | vLLM-Omni | 4 | | | |
+| | | Diffusers | 4 | | | |
+| | | TensorRT-LLM | 4 | 23.04 | 170.63 | 603.31 |
+| | | NIM | 4 | | | |
+| | multi_control | PyTorch | 4 | | | |
+| | | vLLM-Omni | 4 | | | |
+| | | Diffusers | 4 | | | |
+| | | TensorRT-LLM | 4 | 31.56 | 283.95 | 1092.62 |
+| | | NIM | 4 | | | |
+| | seg | PyTorch | 4 | | | |
+| | | vLLM-Omni | 4 | | | |
+| | | Diffusers | 4 | | | |
+| | | TensorRT-LLM | 4 | 23.04 | 167.31 | 608.35 |
+| | | NIM | 4 | | | |
+| | wsm | PyTorch | 4 | | | |
+| | | vLLM-Omni | 4 | | | |
+| | | Diffusers | 4 | | | |
+| | | TensorRT-LLM | 4 | 15.04 | 78.98 | 262.98 |
+| | | NIM | 4 | | | |
+| **H200 NVL** | blur | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 85.61 | 610.21 | 2199.03 |
+| | | Diffusers | 1 | 83.43 | 551.97 | 1935.10 |
+| | | TensorRT-LLM | 1 | | | |
+| | | NIM | 1 | | | |
+| | depth | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 63.72 | 622.24 | 2255.18 |
+| | | Diffusers | 1 | 98.52 | 572.97 | 1970.31 |
+| | | TensorRT-LLM | 1 | | | |
+| | | NIM | 1 | | | |
+| | edge | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 61.97 | 612.63 | 2238.40 |
+| | | Diffusers | 1 | 84.72 | 552.34 | 1940.58 |
+| | | TensorRT-LLM | 1 | | | |
+| | | NIM | 1 | | | |
+| | multi_control | PyTorch | 8 | | | |
+| | | vLLM-Omni | 8 | 57.19 | | 2432.02 |
+| | | Diffusers | 8 | | | |
+| | | TensorRT-LLM | 8 | | | |
+| | | NIM | 8 | | | |
+| | seg | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 62.69 | 614.55 | 2239.94 |
+| | | Diffusers | 1 | 88.16 | 555.93 | 1950.38 |
+| | | TensorRT-LLM | 1 | | | |
+| | | NIM | 1 | | | |
+| | wsm | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 52.06 | 481.65 | 1670.02 |
+| | | Diffusers | 1 | 80.77 | 445.36 | 1470.27 |
+| | | TensorRT-LLM | 1 | | | |
+| | | NIM | 1 | | | |
+| **H200 141GB HBM3** | blur | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 77.82 | 515.99 | 1824.12 |
+| | | Diffusers | 1 | 71.83 | 463.77 | 1593.34 |
+| | | TensorRT-LLM | 1 | 57.89 | 580.64 | 2176.16 |
+| | | NIM | 1 | | | |
+| | depth | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 58.38 | 528.43 | 1875.62 |
+| | | Diffusers | 1 | 84.88 | 481.84 | 1618.53 |
+| | | TensorRT-LLM | 1 | 59.25 | 588.29 | 2193.25 |
+| | | NIM | 1 | | | |
+| | edge | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 55.80 | 527.66 | 1825.62 |
+| | | Diffusers | 1 | 73.22 | 466.10 | 1594.90 |
+| | | TensorRT-LLM | 1 | 58.54 | 580.81 | 2176.79 |
+| | | NIM | 1 | | | |
+| | multi_control | PyTorch | 8 | | | |
+| | | vLLM-Omni | 8 | 58.24 | | |
+| | | Diffusers | 8 | | | |
+| | | TensorRT-LLM | 8 | -0.40 | -0.48 | -0.49 |
+| | | NIM | 8 | | | |
+| | seg | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 57.91 | 528.52 | 1826.29 |
+| | | Diffusers | 1 | 77.09 | 476.15 | 1598.31 |
+| | | TensorRT-LLM | 1 | 58.32 | 571.37 | 2166.54 |
+| | | NIM | 1 | | | |
+| | wsm | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 48.37 | 416.84 | 1406.07 |
+| | | Diffusers | 1 | 70.53 | 382.72 | 1216.43 |
+| | | TensorRT-LLM | 1 | 29.19 | 260.21 | 929.38 |
+| | | NIM | 1 | | | |
+| **B200** | blur | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 42.90 | 264.79 | 943.38 |
+| | | Diffusers | 1 | 42.14 | 241.28 | 789.92 |
+| | | TensorRT-LLM | 1 | 30.02 | 258.30 | 939.00 |
+| | | NIM | 1 | | | |
+| | depth | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 32.81 | 268.01 | 955.14 |
+| | | Diffusers | 1 | 49.41 | 254.68 | 792.02 |
+| | | TensorRT-LLM | 1 | 30.57 | 261.34 | 926.74 |
+| | | NIM | 1 | | | |
+| | edge | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 31.94 | 263.68 | 946.09 |
+| | | Diffusers | 1 | 43.57 | 241.17 | 774.34 |
+| | | TensorRT-LLM | 1 | 29.67 | 258.50 | 919.21 |
+| | | NIM | 1 | | | |
+| | multi_control | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 73.81 | 934.97 | 4038.87 |
+| | | Diffusers | 1 | | | |
+| | | TensorRT-LLM | 1 | 40.45 | 426.01 | 1670.27 |
+| | | NIM | 1 | | | |
+| | seg | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 33.33 | 264.97 | 959.62 |
+| | | Diffusers | 1 | 45.43 | 243.27 | 792.36 |
+| | | TensorRT-LLM | 1 | 29.81 | 257.14 | 925.09 |
+| | | NIM | 1 | | | |
+| | wsm | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 27.64 | 209.59 | 718.19 |
+| | | Diffusers | 1 | 40.66 | 198.30 | 604.37 |
+| | | TensorRT-LLM | 1 | 15.03 | 118.56 | 403.95 |
+| | | NIM | 1 | | | |
+| **B300** | blur | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 44.56 | 251.49 | 863.63 |
+| | | Diffusers | 1 | 39.64 | 226.08 | 720.04 |
+| | | TensorRT-LLM | 1 | 28.84 | 239.51 | 836.14 |
+| | | NIM | 1 | | | |
+| | depth | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 34.74 | 256.94 | 887.06 |
+| | | Diffusers | 1 | 45.83 | 231.26 | 730.46 |
+| | | TensorRT-LLM | 1 | 28.63 | 242.30 | 856.41 |
+| | | NIM | 1 | | | |
+| | edge | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 34.13 | 253.19 | 879.84 |
+| | | Diffusers | 1 | 39.99 | 226.42 | 719.35 |
+| | | TensorRT-LLM | 1 | 28.70 | 243.59 | 835.37 |
+| | | NIM | 1 | | | |
+| | multi_control | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 73.12 | 864.66 | 3687.17 |
+| | | Diffusers | 1 | | | |
+| | | TensorRT-LLM | 1 | 38.82 | 390.38 | 1500.60 |
+| | | NIM | 1 | | | |
+| | seg | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 34.88 | 252.30 | 878.95 |
+| | | Diffusers | 1 | 41.64 | 228.18 | 720.63 |
+| | | TensorRT-LLM | 1 | 28.66 | 239.26 | 834.49 |
+| | | NIM | 1 | | | |
+| | wsm | PyTorch | 1 | | | |
+| | | vLLM-Omni | 1 | 27.58 | 201.45 | 665.09 |
+| | | Diffusers | 1 | 38.40 | 186.76 | 555.47 |
+| | | TensorRT-LLM | 1 | 14.47 | 112.87 | 372.96 |
+| | | NIM | 1 | | | |
+
+Transfer notes:
+1. Values are average generation latency in seconds; lower is better. Diffusers numbers come from PBR `#308587`, vLLM-Omni from PBR `#308574`, and TensorRT-LLM from PBR `#308000`.
+2. The **GPUs** column gives the number of GPUs behind every value in that row, and is the same for every engine in a GPU block so the rows can be compared directly.
+3. PyTorch and NIM have no transfer coverage yet; those rows are unmeasured, not unsupported.
+4. Control hints follow the vLLM-Omni `extra_params` names: `blur`, `depth`, `edge`, `multi_control`, `seg`, and `wsm`. `multi_control` combines several hints in one request.
+
+## Action generation
+
+Forward dynamics is reported separately for AV, camera, and robot inputs. Inverse dynamics and policy are reported for AV and robot because those are the only domain rows in PBR `#308197`; no camera row is inferred. For each domain, PyTorch is populated from that report. vLLM-Omni currently covers forward dynamics AV and inverse dynamics AV from PBR `#308481`. Camera, robot-FD, robot-ID, policy-AV, and policy-robot vLLM-Omni rows remain reserved. **Policy — DROID** is a separate checkpoint and is not mixed with the policy-robot table; this Super page has no Policy-DROID measurements.
+
+### Forward Dynamics — Autonomous Vehicle (AV)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 8 | 59.39 | 59.31 | 59.35 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 11.99 | 22.93 | 23.68 |
+| | TensorRT-LLM | — | | | |
+| **H20** | PyTorch | 8 | 41.51 | 41.47 | 41.42 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 11.40 | 26.98 | 28.79 |
+| | TensorRT-LLM | — | | | |
+| **H100 NVL** | PyTorch | 8 | 21.00 | 21.00 | 21.04 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 10.30 | 19.29 | 20.05 |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 8 | 22.66 | 22.67 | 22.65 |
+| | vLLM-Omni | 1 | 4.33 | 28.78 | 82.08 |
+| | Diffusers | 1 | 27.17 | 53.19 | 51.89 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 10.34 | 12.89 | 13.45 |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | 8 | 14.41 | 14.41 | 14.41 |
+| | vLLM-Omni | 1 | 3.99 | 26.04 | 71.61 |
+| | Diffusers | 1 | 26.51 | 47.34 | 50.20 |
+| | TensorRT-LLM | — | | | |
+| **B200** | PyTorch | 1 | 13.59 | 13.55 | 13.86 |
+| | vLLM-Omni | 1 | 2.37 | 14.59 | 38.41 |
+| | Diffusers | 1 | 4.00 | 16.00 | 16.00 |
+| | TensorRT-LLM | — | | | |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | 2.85 | 14.20 | 36.96 |
+| | Diffusers | 1 | 22.18 | 35.41 | 38.82 |
+| | TensorRT-LLM | — | | | |
+
+### Forward Dynamics — Camera
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 8 | 59.62 | 59.39 | 59.55 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H20** | PyTorch | 8 | 41.13 | 41.10 | 41.11 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H100 NVL** | PyTorch | 8 | 21.05 | 20.98 | 21.00 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 8 | 22.55 | 22.54 | 22.54 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | 8 | 14.30 | 14.30 | 14.29 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **B200** | PyTorch | 1 | 13.73 | 13.72 | 13.58 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+
+### Forward Dynamics — Robot
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 8 | 56.35 | 56.38 | 56.01 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 9.40 | 10.60 | 10.82 |
+| | TensorRT-LLM | — | | | |
+| **H20** | PyTorch | 8 | 15.60 | 15.61 | 15.59 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 8.95 | 10.24 | 10.65 |
+| | TensorRT-LLM | — | | | |
+| **H100 NVL** | PyTorch | 8 | 12.90 | 12.90 | 12.90 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 8.03 | 8.49 | 8.61 |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 8 | 20.16 | 20.15 | 20.15 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 22.21 | 28.53 | 27.35 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 10.27 | 9.04 | 9.25 |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | 8 | 8.74 | 8.74 | 8.70 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 22.02 | 26.45 | 26.38 |
+| | TensorRT-LLM | — | | | |
+| **B200** | PyTorch | 1 | 3.50 | 3.49 | 3.47 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 3.00 | 5.00 | 5.00 |
+| | TensorRT-LLM | — | | | |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 22.21 | 21.81 | 24.51 |
+| | TensorRT-LLM | — | | | |
+
+### Inverse Dynamics — Autonomous Vehicle (AV)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 8 | 59.20 | 59.14 | 59.07 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 11.15 | 23.33 | 23.28 |
+| | TensorRT-LLM | — | | | |
+| **H20** | PyTorch | 8 | 41.17 | 40.96 | 41.06 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 11.33 | 26.66 | 28.46 |
+| | TensorRT-LLM | — | | | |
+| **H100 NVL** | PyTorch | 8 | 20.76 | 21.05 | 20.69 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 9.72 | 18.67 | 20.67 |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 8 | 22.40 | 22.40 | 22.42 |
+| | vLLM-Omni | 1 | 4.36 | 28.21 | 80.85 |
+| | Diffusers | 1 | 15.22 | 44.50 | 43.51 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 10.49 | 12.73 | 13.30 |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | 8 | 14.30 | 14.32 | 14.16 |
+| | vLLM-Omni | 1 | 4.03 | 25.99 | 71.45 |
+| | Diffusers | 1 | 16.58 | 39.75 | 41.71 |
+| | TensorRT-LLM | — | | | |
+| **B200** | PyTorch | 1 | 13.38 | 13.37 | 13.36 |
+| | vLLM-Omni | 1 | 2.42 | 14.69 | 38.74 |
+| | Diffusers | 1 | 4.00 | 16.00 | 16.00 |
+| | TensorRT-LLM | — | | | |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | 1 | 2.69 | 14.44 | 37.70 |
+| | Diffusers | 1 | 15.13 | 26.24 | 28.51 |
+| | TensorRT-LLM | — | | | |
+
+### Inverse Dynamics — Robot
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 8 | 56.28 | 56.33 | 56.00 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 9.59 | 10.90 | 8.71 |
+| | TensorRT-LLM | — | | | |
+| **H20** | PyTorch | 8 | 15.51 | 15.52 | 15.51 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 9.48 | 10.17 | 10.65 |
+| | TensorRT-LLM | — | | | |
+| **H100 NVL** | PyTorch | 8 | 12.51 | 12.51 | 12.51 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 7.92 | 8.46 | 8.79 |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 8 | 20.11 | 20.10 | 20.12 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 12.09 | 16.87 | 18.74 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 8.71 | 8.93 | 9.08 |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | 8 | 8.68 | 8.68 | 8.65 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 25.77 | 16.25 | 16.29 |
+| | TensorRT-LLM | — | | | |
+| **B200** | PyTorch | 1 | 3.42 | 3.49 | 3.41 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 3.00 | 5.00 | 5.00 |
+| | TensorRT-LLM | — | | | |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 9.65 | 15.08 | 15.21 |
+| | TensorRT-LLM | — | | | |
+
+### Policy — Autonomous Vehicle (AV)
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 8 | 59.66 | 59.51 | 59.49 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 12.11 | 22.60 | 25.76 |
+| | TensorRT-LLM | — | | | |
+| **H20** | PyTorch | 8 | 41.54 | 41.51 | 41.49 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 11.35 | 26.61 | 28.81 |
+| | TensorRT-LLM | — | | | |
+| **H100 NVL** | PyTorch | 8 | 21.02 | 21.00 | 21.31 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 9.77 | 18.80 | 20.12 |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 8 | 22.64 | 22.63 | 22.64 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 15.35 | 41.89 | 45.40 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 10.55 | 13.02 | 13.52 |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | 8 | 14.54 | 14.41 | 14.52 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 14.71 | 41.30 | 40.35 |
+| | TensorRT-LLM | — | | | |
+| **B200** | PyTorch | 1 | 13.71 | 13.73 | 13.60 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 4.00 | 16.00 | 16.00 |
+| | TensorRT-LLM | — | | | |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 15.29 | 28.62 | 28.87 |
+| | TensorRT-LLM | — | | | |
+
+### Policy — Robot
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | 8 | 56.31 | 56.29 | 55.95 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 9.57 | 10.08 | 8.76 |
+| | TensorRT-LLM | — | | | |
+| **H20** | PyTorch | 8 | 15.60 | 15.60 | 15.62 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 9.03 | 10.19 | 10.73 |
+| | TensorRT-LLM | — | | | |
+| **H100 NVL** | PyTorch | 8 | 12.56 | 12.55 | 12.54 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 8.05 | 8.60 | 8.89 |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | 8 | 20.16 | 20.17 | 20.16 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 13.82 | 16.92 | 17.03 |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 8 | 8.71 | 9.09 | 9.12 |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | 8 | 8.72 | 8.75 | 8.70 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 11.90 | 16.13 | 14.72 |
+| | TensorRT-LLM | — | | | |
+| **B200** | PyTorch | 1 | 3.48 | 3.49 | 3.48 |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 3.00 | 5.00 | 5.00 |
+| | TensorRT-LLM | — | | | |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | 1 | 10.57 | 15.31 | 15.33 |
+| | TensorRT-LLM | — | | | |
+
+### Policy — DROID
+
+PBR `#308481` measured Policy-DROID only for Cosmos3-Nano-Policy-DROID. Super has no Policy-DROID row in that sweep; this table is reserved.
+
+| GPU | Engine | GPUs | 256p | 480p | 720p |
+|---|---|:-:|---:|---:|---:|
+| **RTX PRO 6000 Blackwell** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H20** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H100 NVL** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H200 NVL** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H100 80GB HBM3** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **H200 141GB HBM3** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **B200** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+| **B300** | PyTorch | — | | | |
+| | vLLM-Omni | — | | | |
+| | Diffusers | — | | | |
+| | TensorRT-LLM | — | | | |
+
+Additional-modality notes:
+1. PyTorch values are average generation (sampling) latency in seconds from PBR `#308197`; lower is better.
+2. PyTorch values use `CUDA_GRAPH=No` and the `latency` automatic-sharding preset.
+3. vLLM-Omni audiovisual values for `t2av`/`t2vs` and `i2av`/`i2vs` are from PBR `#308195`. vLLM-Omni action values are from PBR `#308481`.
+4. Action vLLM-Omni rows report one GPU because the 8-GPU Ulysses runs failed sequence-length divisibility checks.
+5. Policy-DROID is reported in its own table. PBR `#308481` has no Super Policy-DROID measurement.
+6. Diffusers rows are intentionally empty reservations for future benchmark campaigns.
+7. The **GPUs** column gives the number of GPUs behind every value in that row.
+8. Empty cells indicate unmeasured combinations, not unsupported combinations.
\ No newline at end of file