Free API Keys to Call LLMs: A Practical Guide for Developers

So you want to build something with an LLM. Maybe a chatbot, a coding assistant, or just a quick script that summarises your notes. But you open the OpenAI pricing page, see the numbers, and quietly close the tab.

Here's the thing: you don't have to pay a single cent to get started. There are real, working, no-credit-card-required API keys out there right now. This post covers the best ones, what you actually get, and where to grab them. All information was verified as of March 2026.

1. Google Gemini (Best Quality Free Tier)

If you only set up one free API key, make it this one.

Google AI Studio gives you free access to the Gemini 2.5 family of models with no credit card. The free tier covers Gemini 2.5 Pro, Gemini 2.5 Flash, and Gemini 2.5 Flash-Lite.

What you get for free (March 2026):

• Gemini 2.5 Flash-Lite: 15 RPM, 1,000 requests/day (highest free throughput)
• Gemini 2.5 Flash: 10 RPM, 250 requests/day
• Gemini 2.5 Pro: 5 RPM, 100 requests/day
• All models: 250,000 tokens/minute and 1 million token context window

Important note: Google cut free tier quotas by 50-80% in December 2025, so older blog posts citing higher limits are outdated. Gemini 2.0 Flash was deprecated in February 2026 and retired on March 3, 2026. Also be aware that on the free tier, your prompts may be used to improve Google's products.

Get your key: aistudio.google.com/api-keys

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_GEMINI_KEY",
    base_url="https://generativelanguage.googleapis.com/v1beta/openai/"
)

response = client.chat.completions.create(
    model="gemini-2.5-flash",
    messages=[{"role": "user", "content": "Hello!"}]
)

2. Groq (Best for Speed)

Groq is a different beast. It's not about model quality (though the models are solid) -- it's about raw inference speed. We're talking 500 to 700+ tokens per second. That's fast enough that streaming almost feels pointless.

The free developer tier requires no credit card and gives you access to models like Llama 3.3 70B, Llama 4 Scout, Qwen3 32B, and OpenAI's GPT-OSS 120B.

What you get for free:

• 14,400 requests/day and 1,000 RPM on most models
• No time limit on the free tier, it does not expire
• If you exceed rate limits, requests are blocked until the window resets (you are not billed)

Get your key: console.groq.com/keys
Browse models: console.groq.com/docs/models

from langchain.chat_models import init_chat_model

model = init_chat_model(model="llama-3.3-70b-versatile", model_provider="groq")
response = model.invoke("What's the capital of France?")
print(response.content)

Groq is the go-to for agentic pipelines where you're making dozens of LLM calls in a loop. The speed makes it feel snappy instead of painful.

3. OpenRouter (One Key, Many Models)

OpenRouter is a gateway. You get one API key and it routes your requests to dozens of different models. As of March 2026, there are 29 completely free models available, including Llama 3.3 70B, GPT-OSS 120B, DeepSeek R1, Qwen3 Coder 480B, and more.

What you get for free:

• 50 requests/day and 20 RPM with no purchase (enough to test)
• 1,000 requests/day if you have purchased at least $10 in credits at any point (the limit stays even if your balance drops below $10)
• No credit card required to get the base free tier

Browse free models: openrouter.ai/collections/free-models
Get your key: openrouter.ai/workspaces/default/keys

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_OPENROUTER_KEY",
    base_url="https://openrouter.ai/api/v1"
)

response = client.chat.completions.create(
    model="meta-llama/llama-3.3-70b-instruct:free",
    messages=[{"role": "user", "content": "Hello!"}]
)

Note: free model IDs on OpenRouter end in :free. The selection of free models changes over time. The main appeal is flexibility - if you're not sure which model fits your use case, OpenRouter lets you switch without changing your integration.

4. Cerebras (Fastest Inference Available)

Cerebras runs on their custom wafer-scale silicon chips and the speed is genuinely impressive. They claim up to 20x faster throughput than NVIDIA GPUs, with Llama 3.1 8B clocking around 1,800 tokens/second in their benchmarks.

What you get for free:

• 1,000,000 tokens/day (1 million)
• 30 requests/minute and 60,000 tokens/minute
• Models include Llama 3.3 70B, Qwen3 32B, Qwen3 235B, and GPT-OSS 120B
• No credit card required

Get your key: cloud.cerebras.ai

Cerebras is worth having alongside Groq. When you hit Groq's rate limits, switch to Cerebras. Between the two of them, you have more than enough speed and capacity for most agentic projects.

5. Mistral AI (Most Token Volume)

Mistral trains their own models and gives you direct API access for free through their Experiment plan. The plan covers all Mistral models including Mistral Large, Mistral Small 3.1, and Codestral.

What you get for free:

• Approximately 1 billion tokens/month (conservative RPM limits apply - check your dashboard for exact current numbers)
• No credit card required, phone verification needed
• Access to all models in the lineup

Important caveat: API requests made under the Experiment plan may be used to train Mistral's models.

Get your key: console.mistral.ai

The billion tokens/month figure is genuinely massive for prototyping. Mistral Small 3.1 at $0.03 per million input tokens is also one of the cheapest paid models when you do need to upgrade.

6. Cohere (Good for RAG and Embeddings)

Cohere is slightly different from the others - they're particularly strong at embeddings and retrieval-augmented generation (RAG). Their free tier covers Command A, Command R+, and Aya Expanse.

What you get for free:

• 20 requests/minute
• 1,000 requests/month (lower than others, but the models are strong for search and retrieval tasks)
• Embeddings API included at no cost

Get your key: dashboard.cohere.com

If you're building a RAG system and want embeddings plus generation from the same provider, Cohere is worth setting up. The monthly request cap is the main limitation to watch.

7. GitHub Models (Hidden Gem)

If you have a GitHub account, you already have access to this. GitHub Models gives you free access to GPT-4o, GPT-4o mini, Llama 3.3 70B, DeepSeek R1, Phi-4, and more through a playground and API. No separate signup is needed.

What you get for free:

• 50 to 150 requests/day depending on the model tier (Low, High, or Embedding)
• Rate limits vary per model, check the model's marketplace page for details
• Uses your existing GitHub personal access token

Access it: github.com/marketplace/models

The rate limits are tighter than others, so it's best for quick experiments or when you want to test a specific model before committing to a provider. The daily limit is per model, not shared across all models, which helps.

8. Hugging Face Serverless Inference (300+ Models)

Hugging Face's Serverless Inference API gives you access to hundreds of open-source models with a free tier that requires just a Hugging Face account. The free tier is generally limited to models under 10GB, though some larger popular models are included as exceptions.

What you get for free:

• Access to 300+ models
• Rate limits vary by model and are conservative compared to the other providers here
• No credit card required

Get your key: huggingface.co/settings/tokens

Hugging Face is best when you want to experiment with a specific open-source model that is not hosted elsewhere, or when you want to try fine-tuned variants of popular base models.

Bonus: Run It Locally for Free with Ollama

If you have a decent machine, Ollama lets you run models locally - completely free, no rate limits, no API key, and your data never leaves your computer.

# Install Ollama, then pull and run a model
ollama pull llama3.2
ollama run llama3.2

It exposes a local API at http://localhost:11434 that is OpenAI-compatible. The tradeoff is speed: on CPU-only machines, expect 4 to 8 tokens per second with 7B models. On a machine with a decent GPU, it gets much closer to cloud speeds.

Quick Comparison (March 2026)

The Practical Setup

Do not just pick one. Set up all of them on day one. It takes maybe 20 minutes total, and having the keys ready means when you hit a rate limit at 2am, you switch providers in one line of code instead of stopping your work to register somewhere.

A sensible default stack:

• Gemini for anything involving documents, images, or long context (1M token window)
• Groq or Cerebras for fast iteration, agents, and anything that needs quick responses
• OpenRouter as a fallback when you want to try a specific model quickly
• Ollama locally for anything sensitive that should not leave your machine

One honest note: free tiers change. Google cut their limits significantly in late 2025 with no warning. Groq's free tier is still standing as of this writing, but nothing is guaranteed forever. The smart move is to build your code so switching providers takes one line. That way, no single provider holds your project hostage.

The free tiers are genuinely good right now. Stop overthinking it, grab the keys, and start building.