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do small edge boxes make sense with PyTorch
#11
Appreciate the detail. I ended up in about the same place using Ollama. I got better results once I stopped chasing one metric and just looked at whether the workflow felt usable.
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#12
Quote:A couple things I'd check first. Before rebuilding anything, I'd test one clean baseline with Gemma and compare from there. At this point the real bot

I'd approach it in a boring order. If you're on LM Studio, I'd confirm the version first and then reduce variables until the behavior is obvious.
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#13
Good point. I don't think your conclusion is far off. The biggest change for me was simplifying the stack instead of adding one more optimization layer.
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#14
A couple questions before I guess too hard. Is this local-only or are you routing anything externally?
learning in public
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#15
That matches what I was seeing. I don't think your conclusion is far off.
still benchmarking everything
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#16
Quote:A couple questions before I guess too hard. Is this local-only or are you routing anything externally?

Appreciate the detail. The pattern around KV cache pressure 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.
Mostly CUDA, sometimes wrong, usually measured
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