Maybe I'm missing something obvious.

My current setup is TensorRT-LLM with B200, and I keep running into prefill/decode split.

Would appreciate practical advice rather than theory.

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

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

One thing I keep noticing is that people underestimate MoE serving 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.

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.

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

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

Short version: TensorRT-LLM behaved well for me, but only after I stopped ignoring token cost.

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 structured output.

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

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

After a few runs on M3 Max, I ended up with decent performance, but the setup only really made sense once I adjusted around continuous batching.

Happy to post more details if anyone wants them.

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

After a few runs on A6000, I ended up with decent performance, but the setup only really made sense once I adjusted around VRAM headroom.

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

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 long context decides everything downstream.

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

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.

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.

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 INT4 decides everything downstream.

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