How to Set Up OmniRoute: Docker Guide for Free AI API Routing

🐳 How to Set Up OmniRoute in 5 Minutes — A Real Walkthrough

Alright, let's cut the fluff. You want to run OmniRoute, connect your tools to free AI models, and stop paying through the nose for API calls. I'll show you exactly how I did it — including the mistakes I made so you don't repeat them.

Step 1: Spin It Up With Docker

This takes about 30 seconds. I wasted an hour trying to build from source before realizing Docker was the way to go.

docker pull diegosouzapw/omniroute:latest
docker run -d \
  --name omniroute \
  -p 8080:8080 \
  -v ./omniroute-data:/data \
  diegosouzapw/omniroute:latest

Pro tip: I used port 8080 here but if you've got something running on it (looking at you, local WordPress), pick something else. If you see "Address already in use" — docker run -d -p 3000:8080 to map it to port 3000 instead.

Step 2: Connect Claude Code

This is where it gets interesting. Instead of pointing Claude Code directly at Anthropic's API (cha-ching 💸), point it at your local OmniRoute instance:

# Set your OmniRoute endpoint
export ANTHROPIC_BASE_URL=http://localhost:8080/v1
export OPENAI_BASE_URL=http://localhost:8080/v1

# Now Claude Code, Codex, Cursor all use OmniRoute
claude

Wait, that's it? Yep. OmniRoute is a drop-in replacement. Your tools don't know the difference — they just see a standard OpenAI-compatible API endpoint.

Step 3: Access Free Models

This part blew my mind. OmniRoute lists over 50 completely free AI models you can use right now. Here's how to check what's available:

# List available models through OmniRoute
curl http://localhost:8080/v1/models | jq '.data[] | .id'

What I found: Free access to Gemma, Llama variants, some Mistral models, and a bunch of community models. Are they GPT-4 level? No. Are they good enough for prototyping, testing, and light production? Absolutely.

⚡ The Compression Trick That Saves Real Money

OmniRoute's RTK+Caveman compression is enabled by default, but you can tweak it. Here's what I found after a week of testing:

Common Issues I Hit (And How to Fix Them)

❌ "Connection refused" when tools try to reach OmniRoute

Fix: Your tool is probably running on host while OmniRoute is in Docker. Use host.docker.internal:8080 on Mac/Windows, or your actual host IP on Linux. Don't use localhost from inside another container unless they're on the same network.

❌ Free models returning errors

Fix: Free models have rate limits. OmniRoute has auto-fallback — if one free model fails, it tries the next. Give it a few seconds. If it keeps failing, check docker logs omniroute to see which provider is down.

❌ Token counts seem wrong

Fix: The compression changes how tokens are counted. Your bill will be lower, but the reported token count from the model won't match what you're used to. That's expected — trust your wallet, not the counter.

Final Thoughts

I've been running OmniRoute for two weeks now. Cold start is about 2 seconds (the Docker image isn't huge — ~500MB), RAM sits at about 80MB idle, and I haven't had a single crash. For a project this new (it hit 16K stars fast for a reason), it's remarkably stable.

One honest con: the project is evolving quickly and some config options changed between versions. Keep an eye on the repo if you're running in production.

But for saving money on AI APIs? This is the best tool I've found all year.