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Spent some time on this today and wanted to compare notes.
I've gone back and forth between SGLang and PyTorch for Kimi. The interesting difference for me has been continuous batching.
Trying to avoid rebuilding the whole thing twice.
M3 Max • MLX • local-first
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What worked for me was pretty simple. On B200, the easiest win is often to back off the aggressive settings and see whether the problem survives. Not glamorous advice, but repeatable baselines save a lot of time.
7900 XTX / ROCm / somehow still optimistic
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Quote:What worked for me was pretty simple. On B200, the easiest win is often to back off the aggressive settings and see whether the problem survives. Not
A couple things I'd check first. Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at small local stacks. Not glamorous advice, but repeatable baselines save a lot of time.
Mostly CUDA, sometimes wrong, usually measured