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+--- Thread: framework overhead in real deployments (/showthread.php?tid=392)
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framework overhead in real deployments - sparrowcraft - 09-20-2026
Thought I'd post a small recipe because a lot of threads ask similar things.
Just sharing a setup that ended up working reasonably well: Mixtral, PyTorch, mini PC, with a lot of attention on token cost.
Maybe useful as a starting point for newer folks.
Re: framework overhead in real deployments - amberpatch25 - 09-21-2026
A couple things I'd check first. Before rebuilding anything, I'd test one clean baseline with FLUX and compare from there. A lot of these threads end up being one bad config plus a pile of conclusions drawn from it.
Re: framework overhead in real deployments - amberrunner - 09-21-2026
that fixed it for me too.
Re: framework overhead in real deployments - visionforge - 09-21-2026
Need a little more detail here. Are you testing this on M3 Max or something else?
Re: framework overhead in real deployments - rocmrunner40 - 09-21-2026
What exact setup are you running? Is this local-only or are you routing anything externally?
I'm happy to test one more variant if you want a second data point.
Re: framework overhead in real deployments - nanobrook - 09-21-2026
I tested this tonight. My result was mixed: first run looked bad, second run looked normal. I expected the model choice to matter more than it did.
Re: framework overhead in real deployments - embershed99 - 09-21-2026
A couple questions before I guess too hard. Is this local-only or are you routing anything externally?
Re: framework overhead in real deployments - deepseeked - 09-21-2026
I'd approach it in a boring order. Before rebuilding anything, I'd test one clean baseline with Gemma and compare from there.
Re: framework overhead in real deployments - mangovault67 - 09-21-2026
I hit almost the same issue last night.
Re: framework overhead in real deployments - kernelghost - 09-22-2026
Not sure I agree there. I've seen people blame KV cache pressure when the real issue was much more mundane. Worth testing the simpler explanation before adopting the more interesting one.