free-llm-apis

Guide users through obtaining and configuring free API keys for LLM providers. Use when the user wants to set up a free LLM API, get a free API key, connect to a free model provider, configure an OpenAI-compatible endpoint at no cost, or asks about free tiers for AI models. Triggers on "free API key", "free LLM", "set up Gemini/Groq/Mistral/etc.", "which free provider", "how to get an API key", "free model access", "configure LLM for free".

install

source · Clone the upstream repo

git clone https://github.com/mnfst/awesome-free-llm-apis

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/mnfst/awesome-free-llm-apis "$T" && mkdir -p ~/.claude/skills && cp -r "$T/free-llm-apis" ~/.claude/skills/mnfst-awesome-free-llm-apis-free-llm-apis && rm -rf "$T"

manifest: free-llm-apis/SKILL.md

source content

Free LLM API Setup

Help users pick a free LLM provider and configure their API key. Every provider here has a permanent free tier, no credit card needed.

Provider Selection

Ask the user what matters most, then recommend accordingly:

Priority	Best picks
Highest rate limits	Groq (30 RPM, 14.4K RPD), Cerebras (30 RPM, 14.4K RPD)
Largest model selection	Cloudflare Workers AI (49+ models), OpenRouter (32+ models)
Strongest proprietary models	Google Gemini (Gemini 2.5 Pro), GitHub Models (GPT-4o)
Fastest inference	Groq, Cerebras (both optimized for speed)
Highest token budget	Mistral AI (1B tokens/month)
European provider	Mistral AI (EU), LLM7.io (UK)
No signup required	LLM7.io (basic tier works without token)

Provider categories

Provider APIs -- run by the companies that train the models:

Google Gemini, Cohere, Mistral AI, Zhipu AI
See references/provider-apis.md for setup instructions.

Inference providers -- third-party platforms hosting open-weight models:

GitHub Models, NVIDIA NIM, Groq, Cerebras, Cloudflare Workers AI, LLM7.io, Kluster AI, OpenRouter, Hugging Face
See references/inference-providers.md for setup instructions.

Workflow

Ask what models, rate limits, or features the user cares about. If they already know which provider they want, skip to step 3.
Match their priorities against the table above. Suggest 1-2 options with a short reason.
Load the right reference file and walk through the setup steps for that provider (API key, code example, env var).
Offer a quick test script or curl command so they can confirm the key works.

Quick Test Template

After setup, use this to verify any provider:

from openai import OpenAI

client = OpenAI(api_key="KEY", base_url="BASE_URL")

response = client.chat.completions.create(
    model="MODEL_NAME",
    messages=[{"role": "user", "content": "Say hello in one sentence."}],
    max_tokens=50
)
print(response.choices[0].message.content)

Replace KEY, BASE_URL, and MODEL_NAME with values from the provider's setup guide.

Key Notes

All endpoints work with the OpenAI SDK unless noted.
RPM = requests per minute. RPD = requests per day.
Google Gemini's free tier is blocked in the EEA, UK, and Switzerland.
"Limits undocumented" = the provider doesn't publish rate limits.
Don't hardcode API keys. Use environment variables or a secrets manager.