DevQuasar

Looking for some help to test an INT8 Deepseek 3.2:
SGLang supports Channel wise INT8 quants on CPUs with AMX instructions (Xeon 5 and above AFAIK)
https://lmsys.org/blog/2025-07-14-intel-xeon-optimization/

Currently uploading an INT8 version of Deepseek 3.2 Speciale:
DevQuasar/deepseek-ai.DeepSeek-V3.2-Speciale-Channel-INT8

I cannot test this I'm on AMD
"AssertionError: W8A8Int8LinearMethod on CPU requires that CPU has AMX support"
(I assumed it can fall back to some non optimized kernel but seems not)

If anyone with the required resources (Intel Xeon 5/6 + ~768-1TB ram) can help to test this that would be awesome.

If you have hints how to make this work on AMD Threadripper 7000 Pro series please guide me.

Thanks all!

8 replies

csabakecskemeti

posted an update about 1 month ago

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302

Recently there are so much activity on token efficient formats, I've also build a package (inspired by toon).

Deep-TOON

My goal was to token efficiently handle json structures with complex embeddings.

So this is what I've built on the weekend. Feel free try:

https://pypi.org/project/deep-toon/0.1.0/

csabakecskemeti

posted an update about 2 months ago

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2607

Christmas came early this year

3 replies

csabakecskemeti

posted an update 6 months ago

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3068

Has anyone ever backed up a model to a sequential tape drive, or I'm the world first? :D
Just played around with my retro PC that has got a tape drive—did it just because I can.

5 replies

csabakecskemeti

posted an update 7 months ago

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475

Deepseek R1 0528 Q2 locally.
(I believe it has overthinking it a bit :) )
https://youtu.be/Iqu5s9aFaXA?si=QWZe293iTKf_3ELU

DevQuasar/deepseek-ai.DeepSeek-R1-0528-GGUF

csabakecskemeti

posted an update 8 months ago

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2119

Local Llama4 Maverick Q2
https://youtu.be/4F8g_LThli0?si=MGba2SUTHt6xYw3T
Quants uploading now

Big thanks to @ngxson !

csabakecskemeti

posted an update 8 months ago

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1750

Why the 'how many r's in strawberry' prompt "breaks" llama4? :D

Quants DevQuasar/meta-llama.Llama-4-Scout-17B-16E-Instruct-GGUF

3 replies

csabakecskemeti

posted an update 9 months ago

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3421

I'm collecting llama-bench results for inference with a llama 3.1 8B q4 and q8 reference models on varoius GPUs. The results are average of 5 executions.
The system varies (different motherboard and CPU ... but that probably that has little effect on the inference performance).

https://devquasar.com/gpu-gguf-inference-comparison/
the exact models user are in the page

I'd welcome results from other GPUs is you have access do anything else you've need in the post. Hopefully this is useful information everyone.

csabakecskemeti

posted an update 9 months ago

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2412

Managed to get my hands on a 5090FE, it's beefy

| llama 8B Q8_0 | 7.95 GiB | 8.03 B | CUDA | 99 | pp512 | 12207.44 ± 481.67 |
| llama 8B Q8_0 | 7.95 GiB | 8.03 B | CUDA | 99 | tg128 | 143.18 ± 0.18 |

Comparison with others GPUs
http://devquasar.com/gpu-gguf-inference-comparison/

csabakecskemeti

posted an update 9 months ago

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1851

GTC new model announcement now from Nvidia
nvidia/Llama-3_3-Nemotron-Super-49B-v1

GGUFs:
DevQuasar/nvidia.Llama-3_3-Nemotron-Super-49B-v1-GGUF

Enjoy!

csabakecskemeti

posted an update 9 months ago

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597

Cohere Command-a Q2 quant
DevQuasar/CohereForAI.c4ai-command-a-03-2025-GGUF

6.7t/s on a 3gpu setup (4080 + 2x3090)

(q3, q4 currently uploading)

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