What It Is
free-llm-api-resources is a meticulously maintained GitHub repo cataloging every free LLM API available. It's the single most useful resource for developers who want to experiment with LLMs without spending money — from generous free tiers to completely free research APIs.
The Categories
The repo organizes free APIs into practical categories:
- Cloud providers — Google (Gemini free tier), Cloudflare Workers AI, Groq free tier, Together AI trial
- OpenAI-compatible endpoints — Free proxies and alternatives that use the OpenAI SDK format
- Research access — Academic API programs from Anthropic, Google DeepMind, and Meta
- Local alternatives — Tools like Ollama and LM Studio that provide free local inference
- Rate limits and quotas — Clear documentation of what each free tier actually provides (requests/minute, tokens/day)
Why It Matters
The LLM API landscape changes weekly. New providers launch free tiers, existing ones adjust limits, and some disappear entirely. Having a community-maintained directory that tracks these changes is genuinely valuable. Key use cases:
- Students and learners — Start building with LLMs at zero cost
- Prototyping — Validate ideas before committing to paid API plans
- Cost optimization — Route different request types to the cheapest (or free) provider
- Redundancy — When your primary API goes down, knowing free alternatives saves your project
Standout Free Tiers
Some of the most generous free options currently listed:
- Google Gemini Flash — Free tier with generous rate limits, excellent for high-volume tasks
- Groq — Ultra-fast inference with a free developer tier (limited requests/minute)
- Cloudflare Workers AI — 10,000 free neurons/day for inference at the edge
- Cerebras — Free inference API with industry-leading speed for supported models
- OpenRouter — Aggregates free tiers from multiple providers behind one API
This repo is one of those "bookmark it immediately" resources. The difference between a developer who uses this list and one who doesn't is literally hundreds of dollars in API costs during the prototyping phase. More importantly, it lowers the barrier to entry for AI development — you don't need a credit card to start building with LLMs. That accessibility matters for the next generation of AI engineers.