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Thought I'd post a small recipe because a lot of threads ask similar things.
This isn't revolutionary, but the combination of PyTorch and 4090 felt surprisingly usable once I tuned around MoE serving.
Feel free to tear it apart if you see something dumb.
This is mostly for local work rather than public serving.
7900 XTX / ROCm / somehow still optimistic
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Tried to reproduce it just now. On 7900 XTX with Ollama, I saw basically the same behavior. I expected the model choice to matter more than it did.
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Thanks, that helps. That matches what I saw on mini PC. The biggest change for me was simplifying the stack instead of adding one more optimization layer. Turns out 'just one more test' was a lie.
routing beats arguing over one perfect model
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My first guess would be this: If you're on MLX, I'd confirm the version first and then reduce variables until the behavior is obvious. A lot of these threads end up being one bad config plus a pile of conclusions drawn from it.
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Quote:My first guess would be this: If you're on MLX, I'd confirm the version first and then reduce variables until the behavior is obvious. A lot of these
Tried to reproduce it just now. I couldn't reproduce the slowdown until I pushed context much higher. The surprise was that memory pressure showed up before throughput collapsed.
routing beats arguing over one perfect model
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subscribed, curious where this lands.
routing beats arguing over one perfect model
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Ran a quick check on my box. I couldn't reproduce the slowdown until I pushed context much higher. I expected the model choice to matter more than it did.
queue depth watcher
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Thanks, that helps. I ended up in about the same place using LM Studio. The biggest change for me was simplifying the stack instead of adding one more optimization layer.
routing beats arguing over one perfect model
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Appreciate the detail. That matches what I saw on mini PC. The biggest change for me was simplifying the stack instead of adding one more optimization layer.
routing beats arguing over one perfect model