It’s a heavily vibe coded project with only proxy with terrible benchmarks design. Basically vibe coded benchmarks that lie through ignorance of mocked super fast endpoint without using full power of litellm in multiple processes.
Other than that almost useless it’s faster when this will be io bound and not cpu bound.
GoModel. I see some red flags in the docs/benchmarks, but I could be wrong in my judgement here.
What I noticed: the website shows a diagram of the litellm SDK communicating with the gateway proxy of GoModel, poor design of benchmarks, the scope of the project in readme vs. depth.
I don't have professional experience in GoLang, so will not comment on quality of code.
There are some genuinely good things about this project and the effort here, but with solid position of Bifrost sitting at a version above 1.0.0 and so many other initiatives in this space, it's a tough market.
It’s a heavily vibe coded project with only proxy with terrible benchmarks design. Basically vibe coded benchmarks that lie through ignorance of mocked super fast endpoint without using full power of litellm in multiple processes.
Other than that almost useless it’s faster when this will be io bound and not cpu bound.
Which project are you talking about, GoModel or Bifrost?
GoModel. I see some red flags in the docs/benchmarks, but I could be wrong in my judgement here.
What I noticed: the website shows a diagram of the litellm SDK communicating with the gateway proxy of GoModel, poor design of benchmarks, the scope of the project in readme vs. depth.
I don't have professional experience in GoLang, so will not comment on quality of code.
There are some genuinely good things about this project and the effort here, but with solid position of Bifrost sitting at a version above 1.0.0 and so many other initiatives in this space, it's a tough market.
The LiteLLM SDK is intentionally on the website. You can "talk" to GoModel with it because both projects use an OpenAI-compatible API under the hood.
You can use it like this:
Thank you