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Qwen 3.5 397B prompt processing on M3 Ultra (with MLX distributed + JACCL) - 3.4× speedup on 4 chips - scaling improves as context increases Really fun to use with opencode; generated a playable Asteroids clone in ~4 minutes (real time, including me playing it a bit).

23,664 просмотров • 6 месяцев назад •via X (Twitter)

Комментарии: 4

Фото профиля Angelos Katharopoulos
Angelos Katharopoulos6 месяцев назад

Fun fact, the clipping of the video and the plot were actually done with opencode and Qwen 3.5 as well (in parallel actually). I know they are trivial (as is the asteroids game) but when you have it you use it which is pretty fun.

Фото профиля moskstraumen
moskstraumen6 месяцев назад

That's almost linear speedup. Impressive.

Фото профиля Coding at Night
Coding at Night6 месяцев назад

the scaling improving with context length is the interesting part. interconnect overhead gets amortized over longer sequences, which is exactly the regime where local inference matters most.

Фото профиля LightShift Studio
LightShift Studio6 месяцев назад

🚀 Just whipped up an Asteroids clone 🤖!

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Very quick comparison between Ornith 1.5 35B MoE and Qwen 3.8 27B Dense. 📣 Clearly it's not a fair one, but let's in any case see how it went. 397B download in progress! In the Videos below: - Brick SA -> Qwen 3.8 - Lego Streets -> Ornith 1.5 Context: - Pi agent used in both cases, prompt below - M3 Ultra 512GB - Ornith-1.5-35B-A3B-oQ8e MTP hosted on oMLX - mlx-community/Qwen3.8-27B-8bit DFlash 2 hosted on mlx-dspark - Ornith has been incredibly fast with speed from 75 t/s to 45 t/s (160K+ context) - Qwen3.8 suffered context much more reaching 5 t/s above 160K context, but it can be due to engine tested still work in progress - Prompt: using threejs, and cdn, create a lego like game that's inspired by gta san andreas, with beautiful aesthetics and graphics and ability to steal cars. it should be 3d and have a nice and large map and areas. the graphics should be decent and nice. it should feature iconic things from gta san andreas Notes: - Qwen 3.8 result is 0-shot, while Ornith 1.5 required 6 iterations - Ornith 1.5 is not at the same level of autonomy as Qwen 3.8 27B honestly. To try getting the same results I'm constantly nudging, steering and 🤬 at it. - Qwen 3.8 took 6 hours to complete, but it was more a problem of timeout of Chrome headless used for testing, real prefill/decode TBD. I'll test again now with oMLX - Pi agent has a nearly perfect Cache Hit ratio that for local models is MEGA important!

Ivan Fioravanti ᯅ

12,150 просмотров • 1 месяц назад