tashfeenahmed/freellmapi

FreeLLMAPI 7.4 billion tokens per month. 34 free LLM providers. 635 free model endpoints. One OpenAI-compatible endpoint. Aggregate free tiers from dozens of providers, plus custom OpenAI-compatible chat, embedding, image, and audio endpoints, behind a single /v1 API. 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. freellmapi.co · browse the full catalog: 474 model families, 635 free endpoints English · 簡體中文 · Русский Your router updates its own model catalog from a signed feed: new free models, quota changes, and compatibility fixes land without a git pull . Free installs get the monthly snapshot, so a model reaches them 30 days after it joins the live feed; premium routers get it the same day. Go live at freellmapi.co ($19/yr, cancel anytime). Contents Why this exists Supported providers Compatible CLIs & coding agents How it compares Features Quick start Desktop app Works with OpenAI-compatible clients Languages Premium (live catalog) Using the API Screenshots How it works FAQ Limitations Contributing Disclaimer Guides: Install & deploy · API reference · Clients & coding agents · Prompt compression · Architecture & internals · Documentation index · Contributor guide 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 7.4 billion tokens per month of working inference capacity, across 474 model families / 635 provider endpoints from small-and-fast to reasonably capable. The problem is that stacking them by hand is painful: thirty-four different SDKs, thirty-four different rate limits, thirty-four 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. And the free-tier landscape shifts weekly: providers launch models, retire them, and change quotas without notice. FreeLLMAPI tracks all of that for you. The router pulls a signed model catalog from freellmapi.co on its own, so your install keeps up without a git pull . See Premium (live catalog) for how fast it keeps up. Supported providers Google Groq Cerebras OpenCode Zen Mistral OpenRouter Cloudflare Cohere Z.ai (Zhipu) NVIDIA HuggingFace ModelScope Qwen3 · DeepSeek V4 · GLM-5 (needs Aliyun cn binding) … and 22 more free providers Plus a custom provider — point chat, embedding, image, or audio models at any OpenAI-compatible endpoint (llama.cpp, LM Studio, vLLM, a local Ollama, or a remote gateway) from the Keys page. The full, always-current list lives at freellmapi.co/models with per-model rate limits, context windows, and free-token budgets. Compatible CLIs & coding agents Claude Code Codex CLI Gemini CLI Cursor Cline Roo Code OpenCode Aider … plus Continue, Goose, Qwen Code, Kilo Code, Crush, Zed, JetBrains AI, DeepSeek Harness, MiMo Code, AtomCode, OpenClaw, Hermes Agent, Pi, Reasonix and any OpenAI-compatible, Anthropic, Gemini or Ollama client Most agents configure themselves with one command that reads your live catalog, backs up the existing config and merges into it: npx freellmapi setup-claude --url http://localhost:3001 --api-key < unified-key > All supported agents and their setup commands → · Per-tool recipes, MCP server and URL tokens → How it compares Based on public documentation, July 2026 — corrections welcome. Features Every OpenAI-style surface — /v1/chat/completions , /v1/responses (what Codex CLI needs), /v1/completions (editor ghost-text autocomplete), /v1/images/generations , /v1/videos/generations , /v1/audio/speech , /v1/audio/transcriptions , /v1/embeddings , and /v1/models — streaming and non-streaming, from the official SDKs or any OpenAI-compatible client. API reference → Anthropic Messages API — /v1/messages speaks Anthropic's wire format over the same router, so Claude Code and the official Anthropic SDKs run against your free pool. Details → Native Gemini + Ollama surfaces — Gemini CLI can use /v1beta ( generateContent , streaming, token counting, models), while opt-in Ollama emulation serves NDJSON chat/generate, tags, metadata, and embeddings for Zed, JetBrains, and other local-model clients. Fusion (multi-model synthesis) — request the virtual fusion model and the router fans your prompt out to a panel of diverse free models in parallel, then a judge model synthesizes one answer from the drafts. Details → Image, video & speech generation — /v1/images/generations , /v1/videos/generations , and /v1/audio/speech route across the providers that serve media models; images and speech also accept custom OpenAI-compatible media endpoints. Video jobs are normalized across synchronous and queued providers and return a completed MP4. Tool calling & structured outputs — OpenAI-style tools round-trip across providers (plain-text tool calls are rescued into real tool_calls ), plus response_format , seed , logprobs , penalties, and the rest of the sampling params passed through per provider. Smart routing, six strategies — live per-model speed/capability/reliability scores rank your chain; automatic fallover retries the next model on 429/5xx with cooldowns and key rotation. Routing in detail → Unified models & profiles — the same model on several providers collapses into one entry with strict in-group failover; named fallback-chain profiles (a coding chain, a vision chain) switch from the dashboard or per request via auto:<profile> , and custom chains can be renamed in place from the chain manager. Per-key rate tracking — RPM/RPD/TPM/TPD counters per (platform, model, key) that learn providers' reported ceilings, so routing always stays under every cap. Self-updating model catalog — the router syncs a signed catalog from freellmapi.co twice a day: new models, quota changes, and provider quirk fixes land automatically. Free installs track the monthly snapshot, which each model joins 30 days after it lands in the live feed; premium routers get it same-day. Premium → Sticky sessions & context handoff — conversations stay on one model for 30 minutes; an optional compact handoff note keeps the thread coherent when a mid-chat switch does happen. Details → Prompt compression (opt-in) — a shared, fail-open request pipeline can deduplicate prompts, filter tool output, compact repeated JSON, and trim stale context before cache lookup and routing. Details → Encrypted keys, one token out — provider keys are AES-256-GCM encrypted in SQLite and decrypted in-memory per request; your apps only ever see a single unified freellmapi-… bearer token. Admin dashboard & analytics — React UI to manage keys, reorder the chain, run a playground, and read p50/p95/TTFT analytics over 24h–90d windows; login-gated, dark/light themes, 60 languages . ChatGPT-ready MCP server & interactive docs — ChatGPT and other MCP clients can call FreeLLMAPI inference, list usable models, inspect provider health/usage/cache/routing metadata, and manage the routing strategy over /mcp ; a dependency-free OpenAPI viewer lives at /v1/docs . ChatGPT and coding agents → Ops niceties — opt-in response cache, encrypted DB backups, periodic key health checks, bulk key import/export, declarative startup config. Install & deploy → Runs anywhere Node 20+ runs — Windows, macOS, Linux servers, or a small ARM SBC (Raspberry Pi included). ~40 MB RSS at idle behind PM2 / systemd / whatever supervisor you prefer. The scope is deliberately narrow — see what's not supported yet . Quick start One-liner (Docker required — sets up ~/freellmapi , generates an encryption key, pulls the image, and starts the container): curl -fsSL https://freellmapi.co/install.sh | bash Prefer to read before you pipe to bash? The script is here . Re-running it is safe: your .