Free-tier LLM access exists across dozens of providers, but each one has its own API shape, its own rate limits, and its own way of failing when you hit them — which means using free tiers seriously usually means writing (and maintaining) a pile of provider-specific fallback logic yourself. FreeLLMAPI does that consolidation work for you: one OpenAI-compatible endpoint, and it handles picking a provider, routing around rate limits, and rotating keys behind the scenes. FreeLLMAPI aggregates 34 free LLM providers and 635 free model endpoints (about 7.4 billion tokens/month combined) behind a single /v1 API that's OpenAI-compatible, plus support for any custom OpenAI-compatible endpoint. It self-hosts via Docker on macOS, Windows, or a Raspberry Pi with a one-line install, and its router automatically fails over to the next provider when one is rate-limited, rotating keys to stay under each free-tier cap. The model catalog auto-updates from a signed feed, so new free models and quota changes land without a manual update. It supports chat, embeddings, image generation, audio, and video endpoints. It's MIT-licensed, self-hosted and free, with an optional hosted version at $19/year (or $49 lifetime) for faster catalog updates without running your own instance.
| # | Tool | Best for | Price |
|---|---|---|---|
| 1 | Développeurs | — | |
| 2 | Développeurs | — | |
| 3 | Développeurs | — | |
| 4 | Utilisateurs non techniques, équipes commerciales/marketing/RH cherchant à automatiser des workflows répétitifs | — | |
| 5 | Équipes développant des agents IA en production (copilotes, startups SaaS, remplacement de systèmes RAG legacy) | — | |
| 6 | Équipes d'ingénierie et entreprises unifiant l'IA à travers plusieurs outils (Slack, GitHub, Linear, Teams) | — | |
| 7 | Developers and enterprise teams with sensitive data (legal, healthcare, compliance) | — | |
| 8 | Developers building AI agent integrations from existing OpenAPI specs | — | |
| 9 | Enterprise teams needing secure, self-hosted workplace AI search | — | |
| 10 | Small and mid-sized law firms priced out of enterprise legal AI | — | |
| 11 | Développeurs construisant des systèmes multi-agents IA ayant besoin d'un point de coordination public léger | — | |
| 12 | Développeurs voulant intégrer la génération d'images Midjourney dans une app, un SaaS ou un pipeline de contenu | — |
Lets you build automations by describing them in plain English instead of dragging boxes around a workflow canvas, then connects them to tools like Slack, Notion or Google Sheets.
Gives AI agents a real memory and a private workspace so they stop forgetting everything between conversations and re-reading the same documents over and over.
Lets a company build one AI agent that lives inside Slack, GitHub, Linear and other tools it already uses, instead of juggling separate AI features bolted onto each app.
A privacy-first LLM gateway that routes requests across 600+ models without logging prompts, verified via a Trusted Execution Environment.
Turns OpenAPI specs into safe, typed tools that AI agents can call, without manual wiring.
Open-source enterprise AI platform connecting company knowledge across 50+ apps with permission-aware search.
Free, open-source legal AI platform for document review, drafting and legal research.
A public message board built for AI agents rather than humans — any agent can post a note, request, or result by hitting a URL, with zero setup, no SDK, and no account.
An unofficial REST API that lets developers generate Midjourney images from code instead of Discord, with webhooks, polling, and SDKs — since Midjourney itself doesn't offer a public API.
