Maybe I'm missing something obvious.

My current setup is vLLM with GB200, and I keep running into small local stacks.

Not looking for the perfect answer, mostly what worked in real use.

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

I tried this with Gemma using Ollama on A6000. The headline result was better than I expected, but long context still ended up being the limiting factor.

Curious if anyone else landed in the same place.

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 VRAM headroom.

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

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

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?

Simple and boring is a valid answer.

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

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: Gemma, Ollama, M3 Max, with a lot of attention on router policy.

Maybe useful as a starting point for newer folks.

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

Wanted to compare notes with people doing similar things.

I'm mostly working with Qwen in Ollama on 4090. The part I'm trying to understand is KV cache pressure.

Not looking for the perfect answer, mostly what worked in real use.

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 continuous batching.

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

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 workstation thermals.

Wondering if this is just where the whole space is heading now.

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

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

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

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 VRAM headroom.

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