Hey everyone! 👋 I've been diving into the whole fine-tuning/LLM orchestration space and OpenPipe keeps popping up. I'm pretty new to this, so apologies if this is a basic question.
I'm trying to understand where it fits performance-wise. I see a lot of talk about cost and ease-of-use, which is great, but for the project I'm thinking about, latency is going to be super important. We'd be calling a fine-tuned model as part of a user-facing feature.
So my question is: has anyone done or seen any real-world benchmarks comparing OpenPipe's execution speed (like time-to-first-token, total completion time) against other platforms? I'm thinking of places like OpenAI's own fine-tuning, maybe together.ai, or even running something yourself on a cloud instance. I'm not even totally sure what the biggest competitors are yet!
I'm especially curious about:
* If there's a noticeable difference for smaller, simpler fine-tuned models vs. larger ones.
* Whether the speed is consistent or if it varies a lot.
* How much the "cold start" or initialization time factors in, if at all.
The docs talk about performance, but I always find real user experiences more telling. I'm just trying to figure out if the convenience comes with a performance trade-off, or if it's actually snappier. Thanks in advance for any insights!