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Has anyone else run into this?
My current setup is Ollama with M3 Max, and I keep running into small local stacks.
Not looking for the perfect answer, mostly what worked in real use.
For context, I'm not chasing leaderboard numbers. I mostly want the system to feel consistent day to day.
Mostly CUDA, sometimes wrong, usually measured
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What worked for me was pretty simple. Before rebuilding anything, I'd test one clean baseline with Mistral and compare from there. Once you know the plain path works, then add the faster path back in piece by piece.
still benchmarking everything
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Interesting, I hadn't tried that. I ended up in about the same place using TensorRT-LLM. I got better results once I stopped chasing one metric and just looked at whether the workflow felt usable.
image models by night, local pipelines by day
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subscribed, curious where this lands.
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I'd approach it in a boring order. 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.
Mostly CUDA, sometimes wrong, usually measured
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My first guess would be this: On 4090, the easiest win is often to back off the aggressive settings and see whether the problem survives.
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What exact setup are you running? Is this local-only or are you routing anything externally?
