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small speech stack for local use: what are you seeing?
#1
Did a bit of testing and thought I'd post the result here.

Short version: MLX behaved well for me, but only after I stopped ignoring prefill/decode split.

Happy to post more details if anyone wants them.

This is mostly for local work rather than public serving.
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#2
Appreciate the detail. I ended up in about the same place using MLX. I got better results once I stopped chasing one metric and just looked at whether the workflow felt usable.
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#3
What worked for me was pretty simple. On Threadripper box, the easiest win is often to back off the aggressive settings and see whether the problem survives. A lot of these threads end up being one bad config plus a pile of conclusions drawn from it.
image models by night, local pipelines by day
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#4
I hit almost the same issue last night.
local image tinkerer
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#5
Need a little more detail here. Do you see the same thing with a smaller batch or shorter prompt?
learning in public
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#6
I'd approach it in a boring order. On 5090, the easiest win is often to back off the aggressive settings and see whether the problem survives.
curious and caffeinated
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#7
Need a little more detail here. Is this local-only or are you routing anything externally?
image models by night, local pipelines by day
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#8
I'd approach it in a boring order. On GB200, the easiest win is often to back off the aggressive settings and see whether the problem survives. Not glamorous advice, but repeatable baselines save a lot of time.
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#9
A couple things I'd check first. If you're on vLLM, I'd confirm the version first and then reduce variables until the behavior is obvious. Not glamorous advice, but repeatable baselines save a lot of time.
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#10
Not sure I agree there. I've seen people blame tool calling when the real issue was much more mundane. Could be a workload difference, but I wouldn't generalize too fast from one setup.
image models by night, local pipelines by day
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