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speculative decoding in llama.cpp
#1
Posting this in case it saves someone else a little time.

If you were starting from scratch today for this use case, what would you choose first and what would you ignore?

Simple and boring is a valid answer.
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#2
I'd start with the simpler stack.
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#3
Interesting, I hadn't tried that. The pattern around INT4 has been pretty similar for me. I got better results once I stopped chasing one metric and just looked at whether the workflow felt usable.
2x3090 • llama.cpp • too much VRAM is still not enough
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#4
worth checking the driver first.
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#5
same here on my side.
2x3090 • llama.cpp • too much VRAM is still not enough
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#6
subscribed, curious where this lands.

I'm happy to test one more variant if you want a second data point.
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#7
What exact setup are you running? Do you see the same thing with a smaller batch or shorter prompt?
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#8
Did a small comparison this afternoon. On M3 Max with Ollama, I saw basically the same behavior. The main thing that moved was latency, not quality. At this point the real bottleneck is my patience.
2x3090 • llama.cpp • too much VRAM is still not enough
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#9
Interesting, I hadn't tried that. The pattern around token cost has been pretty similar for me.
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