Ollama for power users

[fusedhall]

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

Short version: llama.cpp behaved well for me, but only after I stopped ignoring router policy.

Curious if anyone else landed in the same place.

[vectorember]

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

A couple things I'd check first. If you're on llama.cpp, I'd confirm the version first and then reduce variables until the behavior is obvious.

[visionyard23]

Thanks, that helps. The pattern around embeddings has been pretty similar for me. Worth rechecking your defaults though, because one bad assumption can make the rest of the thread look confusing.

[edgeriver]

Not sure I agree there. I've seen people blame prefill/decode split when the real issue was much more mundane. Could be a workload difference, but I wouldn't generalize too fast from one setup.

[fusedhall]

Need a little more detail here. Do you see the same thing with a smaller batch or shorter prompt? Turns out 'just one more test' was a lie.

[vectorhouse71]

I don't think that's the whole story. I wouldn't optimize around that first. On my side the bigger swing came from the runtime and not the model. Worth testing the simpler explanation before adopting the more interesting one.

[vectorember]

Thanks, that helps. I ended up in about the same place using LM Studio.

[vectorcrate98]

Tried to reproduce it just now. The issue went away once I changed one setting and restarted the stack cleanly.

[quietstack]

Appreciate the detail. I ended up in about the same place using MLX. I got better results once I stopped chasing one metric and just looked at whether the workflow felt usable.

[audionode8]

I hit almost the same issue last night.