# awesome-free-llm-apis

A reference skill listing LLM providers with permanent free tiers, their rate limits, models and Anthropic-compatible setup.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 978 installs · ★ 88
- Author: reason-machines
- License: not stated · policy=link-only · description only; the file stays with the author
- Source: https://github.com/reason-machines/trending-skills/tree/HEAD/skills/awesome-free-llm-apis/SKILL.md
- Updated: 2026-10-09
- HTML: https://affpapa.org/en/nevibecode/skills/awesome-free-llm-apis

## What it does

The skill hands your agent a ready list of providers that offer a permanent free tier for text inference, with no trial credits and no expiry date. Two groups are covered: companies serving their own models (Cohere, Google Gemini, Mistral AI, Zhipu AI) and hosts running open-weight ones (Cerebras, Groq, Cloudflare Workers AI, GitHub Models, Hugging Face, Kluster AI, LLM7.io, NVIDIA NIM, Ollama Cloud, OpenRouter). Each entry carries notable models, request limits and region.

The second half is working code. Python and JavaScript/TypeScript samples show how to point an OpenAI SDK client at a provider by swapping `base_url` and `api_key`. Ollama Cloud is the one endpoint that does not fit that pattern. Keys belong in environment variables such as `GROQ_API_KEY` or `GEMINI_API_KEY`, not in source files.

Read the region and limit columns before you commit. Gemini's free tier does not cover the EU, UK or Switzerland. Zhipu AI and Kluster AI publish no rate limits, so building production traffic on them is a gamble. On OpenRouter the daily cap stays at 50 requests until you have topped up $10, and Hugging Face hands out free credits measured in dollars per month.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add reason-machines/trending-skills --skill awesome-free-llm-apis -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/awesome-free-llm-apis/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/awesome-free-llm-apis/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add reason-machines/trending-skills --skill awesome-free-llm-apis -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/awesome-free-llm-apis/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add reason-machines/trending-skills --skill awesome-free-llm-apis -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/awesome-free-llm-apis/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install reason-machines/trending-skills awesome-free-llm-apis
```

2. **Manually: put the files in place**
- File: `.github/skills/awesome-free-llm-apis/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add reason-machines/trending-skills --skill awesome-free-llm-apis -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/reason-machines/trending-skills --path skills/awesome-free-llm-apis
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/awesome-free-llm-apis/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add reason-machines/trending-skills --skill awesome-free-llm-apis -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/reason-machines/trending-skills/tree/HEAD/skills/awesome-free-llm-apis/SKILL.md

## When to use it
- pick an LLM provider with a permanent free tier
- check rate limits and region before wiring anything up
- repoint an OpenAI SDK client at another provider
- find an OpenAI-compatible endpoint for a prototype
- keep provider keys in environment variables

## Example prompts
- Find me a free LLM API that allows at least 30 requests per minute
- Wire up Groq through the Anthropic SDK and show a minimal Python example
- Which of these free endpoints are Anthropic-compatible and which are not?

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