LocalLLaMA

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Welcome to LocalLLaMA! Here we discuss running and developing machine learning models at home. Lets explore cutting edge open source neural network technology together.

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Grug (caveman compression) of Qwen3.6-35 and 27B is good! (aussie.zone)

submitted 1 month ago* (last edited 1 month ago) by SuspiciousCarrot78@aussie.zone to c/localllama@sh.itjust.works

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Hi all, if you've not heard, there's been a Caveman compression version of Qwen 3.6-27b and Qwen 3.6-35b-3ab.

https://huggingface.co/ProCreations/grug-27b-gguf

https://huggingface.co/ProCreations/grug-35b-v2

https://huggingface.co/ProCreations/grug-35b-v2-gguf

I've been playing around with 35B and I am able to run it on my ancient Quadro P1000 4gb at ~10tok/s.

But beyond that, the quality of the reasoning and the token discipline / output is actually higher than a stock, in my opinion.

You can read the benchmarks above; I am also uploading a HTML file here for your consideration.

(Sorry for the Limewire link; I dunno where else to share throw-away files. It's HTML, though the side by side probably works better if you actually download it)

Anyway...I'm doing more testing right now...but so far, this is a good cook.

Or -

Grug good. Me like.

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[–] SuspiciousCarrot78@aussie.zone 2 points 1 month ago* (last edited 1 month ago) (1 children)

Slight revision: on my rig (i7-8700, 32gb, Quadro p1000 4gb ddr5), this gives a nice 12 tok/s. Unfortunately, it's still hostile to my 1L box and very quickly thermally swamps the CPU (while gpu sits at 56 degrees, that little shit). C'est la vie.

 -t 8 ^
  -tb 8 ^
  -ngl 99 ^
  --n-cpu-moe 38 ^
  --flash-attn on ^
  --no-mmap ^
  --mlock ^
  --cache-type-k q4_0 ^
  --cache-type-v q4_0 ^
  -c 16384 ^
  -b 256 ^
  -ub 128 ^
  --host 0.0.0.0 ^
  --port %PORT% ^
  --ui-mcp-proxy

[–] brucethemoose@lemmy.world 2 points 1 month ago* (last edited 1 month ago)

Be aware, q4_0 KV quantization really borks models.

But the K is far more sensitive than the V. Try q5_1 for the K while leaving the V at q4_0 or q4_1; vram usage will be almost the same, but it should work dramatically better.

As for throttling, try disabling turbo on the 8700.

It doesn’t actually need turbo clocks for these models. The t/s loss I get from doing that on my rig is very modest.

And like others suggested, try the QAT release. You might try the ik_llama.cpp for while you’re at it, at it should be faster with MoEs like this.