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Mindless2112 • yesterday at 11:02 PM • 2 replies • view on HN

As of b8966, it is still not great.

  | model                 |      size |  params | backend | ngl |   test |            t/s |
  | --------------------- | --------: | ------: | ------- | --: | -----: | -------------: |
  | gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | SYCL    | 999 | pp2048 |  851.81 ± 6.50 |
  | gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | SYCL    | 999 |  tg128 |   42.05 ± 1.99 |
  | gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | Vulkan  | 999 | pp2048 | 2022.28 ± 4.82 |
  | gpt-oss 20B MXFP4 MoE | 11.27 GiB | 20.91 B | Vulkan  | 999 |  tg128 |  114.15 ± 0.23 |
  | qwen35 27B Q6_K       | 23.87 GiB | 26.90 B | SYCL    | 999 | pp2048 |  299.93 ± 0.40 |
  | qwen35 27B Q6_K       | 23.87 GiB | 26.90 B | SYCL    | 999 |  tg128 |   14.58 ± 0.06 |
  | qwen35 27B Q6_K       | 23.87 GiB | 26.90 B | Vulkan  | 999 | pp2048 |  581.99 ± 0.86 |
  | qwen35 27B Q6_K       | 23.87 GiB | 26.90 B | Vulkan  | 999 |  tg128 |   10.64 ± 0.12 |
Edit: I've no idea why one would use gpt-oss-20b at Q8, but the result is basically the same:

  | model                 |      size |  params | backend | ngl |   test |            t/s |
  | --------------------- | --------: | ------: | ------- | --: | -----: | -------------: |
  | gpt-oss 20B Q8_0      | 11.27 GiB | 20.91 B | SYCL    | 999 | pp2048 |  854.16 ± 6.06 |
  | gpt-oss 20B Q8_0      | 11.27 GiB | 20.91 B | SYCL    | 999 |  tg128 |   44.02 ± 0.05 |
  | gpt-oss 20B Q8_0      | 11.27 GiB | 20.91 B | Vulkan  | 999 | pp2048 | 2022.24 ± 6.97 |
  | gpt-oss 20B Q8_0      | 11.27 GiB | 20.91 B | Vulkan  | 999 |  tg128 |  114.02 ± 0.13 |
Hopefully, support for the B70 will continue to improve. In retrospect, I probably should have bought a R9700 instead...

Replies

jaimie • today at 5:05 AM

"I've no idea why one would use gpt-oss-20b at Q8" - would you mind expanding on this comment?

In that particular model family, the choices are 20B and 120B, so 20B higher quant fits in VRAM, while you'd be settling for 120B at a lower quant. Is it that 20B MXFP4 is comparable in performance so no need for Q8?

Or is the insight simply that there are better models available now and the emphasis is on gpt-oss-20b, not Q8?

➕ show 1 reply
ycui7 • today at 7:31 AM

At this speed, people end up paying more on electricity than api calls. (California electricity)