I figured I'd ask here before changing everything.

I'm mostly working with Qwen in MLX on GB200. The part I'm trying to understand is NVFP4.

If you've tested something similar, what did you keep and what did you stop bothering with?

For context, I'm not chasing leaderboard numbers. I mostly want the system to feel consistent day to day.

I'm trying to sanity-check my setup.

I'm trying to decide whether to keep the current stack or change course. Main question is how people here are handling tool calling.

Would appreciate practical advice rather than theory.

I care more about stability than squeezing the last possible tokens/sec out of it.

I expected the biggest difference to come from the model, but the stack around it mattered at least as much.

Posting this in case it saves someone else a little time.

I'm helping a small team set up a local workflow. We don't need a giant stack, but we do care about embeddings.

Would rather learn from your scars than collect my own all at once.

Spent some time on this today and wanted to compare notes.

I've gone back and forth between llama.cpp and PyTorch for FLUX. The interesting difference for me has been long context.

Trying to avoid rebuilding the whole thing twice.

This keeps coming up in conversation so I figured I'd start a thread.

The more I work with local setups, the more it seems like continuous batching decides everything downstream.

Curious whether that lines up with what other people are seeing.

Did a bit of testing and thought I'd post the result here.

After a few runs on mini PC, I ended up with decent performance, but the setup only really made sense once I adjusted around quant drift.

Happy to post more details if anyone wants them.

Spent some time on this today and wanted to compare notes.

Two paths both seem viable, but they break down differently once workstation thermals becomes important.

What would you pick if you had to live with it for a few months?

Maybe I'm missing something obvious.

My current setup is TensorRT-LLM with B200, and I keep running into speculative decoding.

If you've tested something similar, what did you keep and what did you stop bothering with?

My use case is pretty ordinary: local chat, some document work, and occasional batch jobs.

Posting this in case it saves someone else a little time.

If you were starting from scratch today for this use case, what would you choose first and what would you ignore?

I'm especially interested in mistakes worth avoiding.

Did a bit of testing and thought I'd post the result here.

After a few runs on mini PC, I ended up with decent performance, but the setup only really made sense once I adjusted around router policy.

Happy to post more details if anyone wants them.

I care more about stability than squeezing the last possible tokens/sec out of it.