LiteLLM vs AegisFlow: honest comparison from someone who built the alternative

I built AegisFlow because I needed an LLM proxy and kept running into things with LiteLLM that didn't work for me. This isn't a takedown. LiteLLM has a huge community, 100+ providers, and a lot of teams use it in production. But I wanted something different, so I wrote my own in Go. Here's what I found after using both. Where LiteLLM is the better choice Provider count. LiteLLM supports over 100 providers. AegisFlow supports 10. If you need Sagemaker, VertexAI, or NVIDIA NIM out of the box, LiteLLM is the answer and it's not close. Python. If your whole team writes Python, LiteLLM is pip install litellm and you're running. AegisFlow is a Go binary. Your Python devs can talk to it over HTTP, but the project itself isn't in their language. Endpoint coverage. LiteLLM handles embeddings, images, audio, batches, reranking. AegisFlow only does chat completions and model listing. If you need multimodal endpoints, LiteLLM has them. Community. LiteLLM has thousands of users. AegisFlow just got