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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 fa
by lackoftactics 6mo ago
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.
- eikenberry 6mo agoWhich project are you talking about, GoModel or Bifrost?
- lackoftactics 6mo agoGoModel. 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.
- santiago-pl 6mo agoThe 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: from litellm import completion print(completion( model="openai/gpt-4.1-nano", api_base="http://localhost:8080/v1", api_key="your-gomodel-key", messages=[{"role": "user", "content": "hi"}], ).choices[0].message.content)
- lackoftactics 6mo agoThank you