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speculative decoding in llama.cpp
#11
Thanks, that helps. I don't think your conclusion is far off. I got better results once I stopped chasing one metric and just looked at whether the workflow felt usable.

I'm happy to test one more variant if you want a second data point.
Apple Silicon • MLX mostly
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#12
I'd start with the simpler stack.
mostly local
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#13
What worked for me was pretty simple. On M3 Max, the easiest win is often to back off the aggressive settings and see whether the problem survives. Once you know the plain path works, then add the faster path back in piece by piece.
image models by night, local pipelines by day
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