I figured I'd ask here before changing everything.

I'm mostly working with Llama in Ollama on 7900 XTX. The part I'm trying to understand is workstation thermals.

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

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

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

I've gone back and forth between LM Studio and TensorRT-LLM for Mistral. The interesting difference for me has been prefix caching.

Trying to avoid rebuilding the whole thing twice.

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

I'm comparing two approaches here: keep it simple on 4090, or squeeze more out of the stack and deal with the complexity.

Interested in tradeoffs more than fan loyalty.

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.

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

I'm comparing two approaches here: keep it simple on B200, or squeeze more out of the stack and deal with the complexity.

Trying to avoid rebuilding the whole thing twice.

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: Phi, llama.cpp, A6000, with a lot of attention on reranking.

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

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

I'm comparing two approaches here: keep it simple on A6000, or squeeze more out of the stack and deal with the complexity.

Trying to avoid rebuilding the whole thing twice.

I figured I'd ask here before changing everything.

My current setup is Ollama with dual 3090, and I keep running into router policy.

Would appreciate practical advice rather than theory.

This is mostly for local work rather than public serving.

If I had to summarize the lesson so far, it would be that clean setup and observability beat clever guesses.

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 MLX and mini PC.

I'm especially interested in mistakes worth avoiding.

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.

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

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

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