I built a single API to access 170+ AI models — here's why

I got tired of juggling API keys.

Every time I wanted to test a new model — switch from GPT-4o to Claude, or try a Qwen variant — I had to manage separate accounts, separate billing, separate rate limits. For a solo developer, that overhead adds up fast.

So I built TokenMix.ai.

The idea is simple: one OpenAI-compatible endpoint, 170+ models behind it. You point your existing code at api.tokenmix.ai, swap the model name, and that's it. No SDK changes, no refactoring.

client = OpenAI( base_url="https://api.tokenmix.ai", api_key="your_key" )

Why this matters for builders

When you're prototyping, you don't want to commit to one model upfront. Different tasks call for different models — Claude tends to be better for writing, GPT-4o for structured outputs, smaller open-source models for high-volume cheap tasks. Being able to benchmark them with the same code in 5 minutes changes how you build.

Pay-as-you-go, no monthly fees. You pay for what you use. Good for early-stage projects where traffic is unpredictable.

Where we are now

Still early. 170+ models live, 99.9% uptime target, actively adding more. Looking for feedback from developers actually building with it — what models are missing, what's broken, what would make this actually useful for your workflow.

If you're doing anything with AI APIs, give it a try and let me know what you think.

→ tokenmix.ai