Aggregate the free tiers from Google, Groq, Cerebras, SambaNova, NVIDIA, Mistral, OpenRouter, GitHub Models, Hugging Face, Cohere, Cloudflare, Zhipu, Moonshot, and MiniMax behind a single `/v1/chat/completions` endpoint. Keys are stored encrypted. A router picks the best available model for each request, falls over to the next provider when one is rate-limited, and tracks per-key usage so you stay under every free-tier cap.
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## Why this exists
Every serious AI lab now offers a free tier — a few million tokens a month, a few thousand requests a day. On its own each tier is a toy. Stacked together, they add up to roughly **800 million tokens per month** of working inference capacity, across dozens of models from small-and-fast to reasonably capable.
Every serious AI lab now offers a free tier — a few million tokens a month, a few thousand requests a day. On its own each tier is a toy. Stacked together, they add up to roughly **1.3 billion tokens per month** of working inference capacity, across dozens of models from small-and-fast to reasonably capable.
The problem is that stacking them by hand is painful: fourteen different SDKs, fourteen different rate limits, fourteen places a request can fail. FreeLLMAPI collapses that into one OpenAI-compatible endpoint. Point any OpenAI client library at your local server, and it routes transparently across whichever providers you've added keys for.
