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

I tried this with Phi using SGLang on M3 Max. The headline result was better than I expected, but structured output still ended up being the limiting factor.

Nothing scientific here, just practical notes from a real setup.

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

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 tokens/sec decides everything downstream.

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

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

Thought I'd post a small recipe because a lot of threads ask similar things.

This isn't revolutionary, but the combination of LM Studio and 5090 felt surprisingly usable once I tuned around quant drift.

If someone wants the exact settings I can clean them up and post them.

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

I tried this with DeepSeek using LM Studio on 5090. The headline result was better than I expected, but tokens/sec still ended up being the limiting factor.

Curious if anyone else landed in the same place.

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

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

It feels like the conversation has shifted hard toward inference and serving details lately, and honestly that makes sense once you start dealing with KV cache pressure.

Maybe obvious to some of you, but it clicked for me this week.

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 mostly working with FLUX in PyTorch on mini PC. The part I'm trying to understand is router policy.

Would appreciate practical advice rather than theory.

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

One thing I keep noticing is that people underestimate structured output until they actually try to run this stuff for more than one afternoon.

Maybe obvious to some of you, but it clicked for me this week.

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

Short version: Ollama behaved well for me, but only after I stopped ignoring workstation thermals.

Nothing scientific here, just practical notes from a real setup.

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

I'm not trying to build a perfect architecture diagram. I just want a sane starting point around SGLang and Threadripper box.

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'm comparing two approaches here: keep it simple on M3 Max, or squeeze more out of the stack and deal with the complexity.

Trying to avoid rebuilding the whole thing twice. The logs were somehow calmer than I was.