Thread Rating:
  • 0 Vote(s) - 0 Average
  • 1
  • 2
  • 3
  • 4
  • 5
Tensor cores actually helping here
#1
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: FLUX, MLX, 4090, with a lot of attention on router policy.

Maybe useful as a starting point for newer folks. I keep promising myself this is the last rebuild.
Reply
#2
that fixed it for me too.
Reply
#3
I'd approach it in a boring order. Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at KV cache pressure. Not glamorous advice, but repeatable baselines save a lot of time.

There are a few different conversations hiding inside this thread, so being explicit about the goal helps.
Reply
#4
Interesting, I hadn't tried that. The pattern around speculative decoding has been pretty similar for me. The biggest change for me was simplifying the stack instead of adding one more optimization layer.
Reply
#5
Quote:Interesting, I hadn't tried that. The pattern around speculative decoding has been pretty similar for me. The biggest change for me was simplifying th

Ran a quick check on my box. My result was mixed: first run looked bad, second run looked normal. The main thing that moved was latency, not quality.
LoRA tinkerer • dataset janitor
Reply
#6
I think the bottleneck is somewhere else. I wouldn't optimize around that first. On my side the bigger swing came from the runtime and not the model. Worth testing the simpler explanation before adopting the more interesting one.
Reply


Forum Jump:


Users browsing this thread: 1 Guest(s)