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batch12 | 1 month ago

Could they have added some swap?

discuss

order

geerlingguy|1 month ago

No, just updated the parent comment, I added -c 4096 to cut down the context size, and now the model loads.

I'm able to get 6-7 tokens/sec generation with 10-11 tokens/sec prompt processing with their model. Seems quite good, actually—much more useful than llama 3.2:3b, which has comparable performance on this Pi.

Aurornis|1 month ago

> I added -c 4096 to cut down the context size

That’s a pretty big caveat. In my experience, using a small context size is only okay for very short answers and questions. The output looks coherent until you try to use it for anything, then it turns into the classic LLM babble that looks like words are being put into a coherent order but the sum total of the output is just rambling.

layoric|1 month ago

Thanks for posting the performance numbers from your own validation. 6-7 tokens/sec is quite remarkable for the hardware.

nallic|1 month ago

for some reason I only get 3-4 tokens/sec. I checked the CPU does not throttle or anything.