[Benchmark] RX 7900 XTX 24 GB (gfx1100), Windows: 0.2.0-beta hip-rdna3 package vs 0.1.44.1, and the GPU vision encoder (Qwen3.8-Flash-Next IQ3_XXS) #3383

What did you measure, or what went wrong

The windows-x86_64-hip-rdna3 package of 0.2.0-beta on an RX 7900 XTX, against 0.1.44.1 on the same machine, model and config. Measured on 2026-10-20. Main limitation: two runs per variant, one card, and a large download was writing to the model drive during the runs (about 60 MB/s), so all numbers are ~5-10% below what this box does on a quiet night, on both sides.

Hardware and software

• GPU: AMD Radeon RX 7900 XTX 24 GB (gfx1100); CPU: Ryzen 9 7900X3D; RAM: 64 GB; model files on a PCIe 4 NVMe.
• OS: Windows 11 Pro 26100.
• A: Strata 0.1.44.1 (strata-windows-x64-hip.zip from the v0.1.44.1 release).
• B: Strata 0.2.0-beta, engine 0.1.45.3 (strata-engine-0.1.45.3-windows-x86_64-hip-rdna3.tar.gz, SHA-256 checked; BUILD.json: commit 18f7b90, rocm 10.2.0a20260930, hipblaslt_version 100500). The log shows prefill gemm: hipBLASLt tuning enabled (32 rows, gfx1100, version 100500), so the tuned tables are in the package and used.
• Model: Qwen3.8-Flash-Next GSQ-RCO IQ3_XXS, native pack iq3_xxs, expert profile data/expert-profile.bin (24576 ranked pairs).

Config (same for A and B)

strata.exe --serve --pack <pack> --native <gguf 1 of 2> --ple-gguf <gguf 2 of 2> --expert-profile <expert-profile.bin>
  --expert-cache auto --prefill auto --spec 4 --spec-min-p 0.5 --mtp <mtp/rt> --max-context 131072 --kv int8
  --kv-resident 131072 --short-read 512 --vision --vram-reserve-mib 1536
  --conversation-cache-mib 4096 --conversation-cache-slots 2
  (+ the experimental speed projection control vector, layers 4-44)

Method

One fresh engine per session, A and B alternated (A, B, A, B). Each session: a 20-token warm-up, then fresh prompts (unique text, 0 reused), additions to the same conversation, a 300-token story, and in a second session a fresh 26K prompt and two pictures (an invoice, a chart). Times are client-side, speeds are the engine's prompt ... tok/s / generated ... tok/s.

Results (run 1 / run 2)

No measurable difference between A and B on this card: the spread between two runs of the same build is as large as the gap between builds.

GPU vision encoder of 0.2.0-beta (strata-vision-hip.exe, log: warmed up at 289 image tokens) against the CPU encoder (12 threads), engine B, same config, alternated:

About 3 s faster on documents, nothing on the photo, and ~750 fewer expert-cache slots, with no visible effect on decode here. Answers to the pictures were right with the GPU encoder.

Poor results and failed requests

• The CPU run 2 (numbers in brackets) came up in the bad start state of [Engine] Windows HIP, one RX 7900 XTX: about 1 engine start in 10 answers long prompts and pictures wrong (KV streaming 0 block reads), still in 0.2.0-beta #2960: all three picture answers were about some other picture, so its times don't count. In the speed bench, run 1 of A (its long session, numbers in brackets) also answered the 26K prompt wrong, same defect. Details and logs in [Engine] Windows HIP, one RX 7900 XTX: about 1 engine start in 10 answers long prompts and pictures wrong (KV streaming 0 block reads), still in 0.2.0-beta #2960.

Reproduction status

Measured locally