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geerlingguylast Tuesday at 11:38 PM3 repliesview on HN

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.


Replies

Aurornislast Wednesday at 12:40 PM

> 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.

layoriclast Tuesday at 11:47 PM

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

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nalliclast Wednesday at 12:43 PM

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