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Why your local LLM feels dumber than it is

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Re: Why your local LLM feels dumber than it is

#231

Earlier quoted context omitted.

If I use the 12B Unified (dense) model I mentioned without MTP, then I get 37t/s, input ~700t/s. It's all still quite frustrating in the end, like a Claude from a very long time ago by now but usable. If I want 64k context, I can't use MTP. I still haven't decided whether I'd rather have 37t/s but it's "less dumb" or I want MTP speed but it's going off the rails more. All of this is also with `-ctv q4_0 -ctk q4_0)`,…

Haha, OK, so it processes input tokens at 55t/s if started like the 12B. That's so slow that I don't even have the patience to wait for the context of the session I aborted mid-processing to test this, to load. Heck loading the system prompt alone is not fun. That said, after that it seems to run at the same ~35t/s speed but , I was able to start it up with a 128k context (and no KV quantization), humm humm. I am now…

Thank you, very interesting to read. I haven't considered batch sizes at all up to now. Seems I should look into it.

How did you get the prediction that good? The default spec-draft-max-n is 3 and if I go beyond, the output rate stays the same or gets lower any magic spell you could share?

Re: Why your local LLM feels dumber than it is

#232

Earlier quoted context omitted.

Haha, OK, so it processes input tokens at 55t/s if started like the 12B. That's so slow that I don't even have the patience to wait for the context of the session I aborted mid-processing to test this, to load. Heck loading the system prompt alone is not fun. That said, after that it seems to run at the same ~35t/s speed but , I was able to start it up with a 128k context (and no KV quantization), humm humm. I am now…

Thank you, very interesting to read. I haven't considered batch sizes at all up to now. Seems I should look into it. How did you get the prediction that good? The default spec-draft-max-n is 3 and if I go beyond, the output rate stays the same or gets lower any magic spell you could share?

Wow, setting the "ubatch" size to 2048 (default is 512), like the "batch" size roughly doubled prompt processing speed.

Re: Why your local LLM feels dumber than it is

#233

Earlier quoted context omitted.

Haha, OK, so it processes input tokens at 55t/s if started like the 12B. That's so slow that I don't even have the patience to wait for the context of the session I aborted mid-processing to test this, to load. Heck loading the system prompt alone is not fun. That said, after that it seems to run at the same ~35t/s speed but , I was able to start it up with a 128k context (and no KV quantization), humm humm. I am now…

Thank you, very interesting to read. I haven't considered batch sizes at all up to now. Seems I should look into it. How did you get the prediction that good? The default spec-draft-max-n is 3 and if I go beyond, the output rate stays the same or gets lower any magic spell you could share?

Regarding the MTP, if you haven't found out why yet, the `--spec-draft-p-min 0.8`. Something to play with and of course it's non-deterministic and depends on both the model itself and whatever you're actually throwing at it.

This is what I read before I went to try it: https://github.com/ggml-org/llama.cpp/discussions/25198

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