GPT-Load is a self-hosted AI gateway that unifies access to multiple LLM providers and credentials behind one endpoint. Written in Go, it handles multi-channel routing, API key pools, scheduling, failover and usage logging for tools and agents that speak the OpenAI, Claude or Gemini formats. The project has about 7,200 stars on GitHub and is actively developed in 2026.
Anyone running several AI tools quickly accumulates a mess of provider accounts, keys and subscription logins, each with its own limits. GPT-Load sits in front of all of them: you register channels and credentials once, and the gateway distributes requests across them with load balancing and priority scheduling, automatically failing over when a key hits a rate limit or an upstream errors out. Invalid keys are detected and benched, request logs and per-key usage statistics are kept for auditing, and clients keep using a single base URL and token. It supports the OpenAI, Anthropic and Gemini API formats so coding agents and chat tools can share the same pool, and it deploys as a single Go service with a web admin panel โ a practical fit for a home lab or a small team’s shared AI infrastructure. The project is MIT licensed.
GPT-Load is free and open source under the MIT license. You only pay for the upstream model accounts and API usage you connect to it.
GPT-Load is for developers and small teams juggling multiple LLM accounts and keys who want one reliable, observable gateway for their AI tools and agents instead of per-app configuration.