TL;DR: I migrated a production LLM workload from LiteLLM to Bifrost and the swap took about 30 minutes for the gateway, plus a few config translations. The OpenAI-compatible endpoint means application code did not change. This post walks through the full migration: config mapping, virtual key translation, semantic cache porting, and the gotchas I hit.

This post assumes familiarity with LiteLLM proxy mode, OpenAI-compatible APIs, and basic Docker or Node.js operations.

Why Teams Are Looking at the Migration

LiteLLM is the most widely adopted open-source LLM gateway and covers the breadth case well. The reasons I see teams move to Bifrost are usually one of three:

Latency overhead. LiteLLM proxy adds roughly 8 milliseconds per request. Bifrost adds 11 microseconds at P99 latency at 5k RPS, which is 50x lower. For high-throughput agent workloads that matters.

MCP support. LiteLLM does not have MCP gateway functionality.…