[rvz]

I don't see any significant advantage over mature routers like Bifrost.

Are there even any benchmarks?

[santiago-pl]

My thoughts about this:

Benchmarking AI gateways properly is harder than it looks. Feature sets differ meaningfully - exact vs semantic caching, cluster mode, guardrails, audit logging - and each carries its own latency cost. What actually matters for most users is end-to-end latency including provider overhead (200–2000ms), and in that frame Bifrost, LiteLLM, and GoModel are all perfectly fine.

I ran some comparisons but I'm not happy with the methodology, and I'd rather not spread misleading information. Once I have time to do it properly I'll write it up and share a link here. Honestly, I'd also love to see benchmarks done by someone other than the AI gateway builders. :)

Where GoModel actually differs today:

  - image size: 16.96 MB vs Bifrost's 69.84 MB. It matters for sidecar, edge, and cold-start scenarios.
  - per-tenant keys, guardrails, and audit logs are all in the OSS repo - not gated.
  - AI interaction visualization that makes debugging individual request/response flows much easier.

[lackoftactics]

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]

Which project are you talking about, GoModel or Bifrost?

[lackoftactics]

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.

[santiago-pl]

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:

  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]

Thank you