gpt-load

GPT-Load puts one base URL and one access key in front of every model provider you use. Your app stops caring whether a request lands on OpenAI, Anthropic, Gemini, Bedrock, or Groq. Channels, credentials, models, and routing policy all live in a web console. MIT, Go, free.

Deployment is Docker Compose with application-managed SQLite by default, MySQL or Postgres if you outgrow it. It binds to localhost, the right default for something holding every API key you own, so budget time for TLS and firewall work before exposing it. One file matters most: the encryption.key file decrypts all stored credentials, this version cannot rotate it, and losing it makes every saved credential unrecoverable.

Solo devs with a single API key do not need this. Small teams running several providers who want per-key usage and cost visibility are the sweet spot. Above that, read the fine print: 2.0 runs as a single instance and shares no state, so horizontal scaling is off the table. LiteLLM is the better call at that size.

The catch is the feature that draws the traffic. Alongside API keys, GPT-Load pools subscription accounts through OAuth, Codex, Claude, Antigravity, and Grok, behind one endpoint. Those flows are unofficial and can break whenever an upstream changes, and the README itself tells you to connect only accounts you are entitled to use. That is the real constraint, not boilerplate.