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

Two paths both seem viable, but they break down differently once batch size becomes important.

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.

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

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

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?

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 B200, 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.

I'm mostly working with Llama in llama.cpp on M3 Max. The part I'm trying to understand is tool calling.

Would appreciate practical advice rather than theory.

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.

I'm not trying to build a perfect architecture diagram. I just want a sane starting point around TensorRT-LLM and B200.

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

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

After a few runs on GB200, I ended up with decent performance, but the setup only really made sense once I adjusted around small local stacks.

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

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?

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 mini PC, or squeeze more out of the stack and deal with the complexity.

Trying to avoid rebuilding the whole thing twice.

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 structured output.

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