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I'm trying to sanity-check my setup.
I'm trying to decide whether to keep the current stack or change course. Main question is how people here are handling small local stacks.
Not looking for the perfect answer, mostly what worked in real use.
I care more about stability than squeezing the last possible tokens/sec out of it.
still benchmarking everything
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Did a small comparison this afternoon. I couldn't reproduce the slowdown until I pushed context much higher. I expected the model choice to matter more than it did.
trying not to rebuild again
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Thanks, that helps. I ended up in about the same place using SGLang. The biggest change for me was simplifying the stack instead of adding one more optimization layer.
learning in public
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I'd start with the simpler stack.
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that fixed it for me too.
small models can still be useful
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Good point. The pattern around router policy has been pretty similar for me.
M3 Max • MLX • local-first
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I tested this tonight. The issue went away once I changed one setting and restarted the stack cleanly. The main thing that moved was latency, not quality.
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My first guess would be this: If you're on PyTorch, I'd confirm the version first and then reduce variables until the behavior is obvious. Once you know the plain path works, then add the faster path back in piece by piece.
small models can still be useful
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Thanks, that helps. That matches what I saw on GB200.
mostly local