Best Free Open Source LLM APIs in 2026

You do not need to spend hundreds of dollars a month to build AI-powered applications. The open-source LLM ecosystem in 2026 offers high-quality models with free or extremely affordable API access. Whether you are prototyping, building side projects, or running production workloads on a budget, these APIs give you powerful language models without breaking the bank.

This guide covers the best free and open-source LLM APIs available right now, with pricing, rate limits, and code examples for each.

Quick Comparison

Provider	Free Tier	Top Model	Context Window	Rate Limit (Free)	OpenAI Compatible
Groq	Yes	Llama 3.3 70B, DeepSeek R1	128K	30 req/min	Yes
Together AI	$5 free credit	Llama 3.3 70B, Qwen 2.5 72B	128K	60 req/min	Yes
Fireworks AI	$1 free credit	Llama 3.3 70B, Mixtral	128K	10 req/min	Yes
OpenRouter	Some free models	Varies by model	Varies	Varies	Yes
HuggingFace Inference	Free (rate limited)	Llama 3.3, Mistral, Qwen	32K-128K	60 req/hr	Partial
Cerebras	Free beta	Llama 3.3 70B	128K	30 req/min	Yes
SambaNova	Free tier	Llama 3.3 70B	128K	20 req/min	Yes
Ollama (local)	Free forever	Any GGUF model	Depends on RAM	Unlimited	Yes
Google AI Studio	Free tier	Gemini 2.5 Flash	1M	15 req/min	No (own SDK)
Cloudflare Workers AI	Free tier	Llama 3.3, Mistral	32K	10K req/day	Partial

1. Groq

Groq offers the fastest LLM inference available, running models on their custom LPU (Language Processing Unit) hardware. Their free tier is one of the most generous.

Free Tier Details

Feature	Limit
Rate limit	30 requests/minute, 14,400 requests/day
Models available	Llama 3.3 70B, DeepSeek R1, Mixtral 8x7B, Gemma 2
Token limits	~6,000 tokens/minute (varies by model)
Context window	Up to 128K tokens

Setup

# Get API key from console.groq.com
export GROQ_API_KEY="gsk_xxxxxxxxxxxx"

from openai import OpenAI

client = OpenAI(
    api_key="gsk_xxxxxxxxxxxx",
    base_url="https://api.groq.com/openai/v1"
)

response = client.chat.completions.create(
    model="llama-3.3-70b-versatile",
    messages=[{"role": "user", "content": "Explain quicksort in Python"}],
    temperature=0.7
)
print(response.choices[0].message.content)

Why Use Groq

Fastest inference speeds in the industry. Responses come back in milliseconds rather than seconds. The free tier is generous enough for prototyping and personal projects.

2. Together AI

Together AI hosts a wide range of open-source models with competitive pricing and a $5 free credit for new accounts.

Free Credit Details

Feature	Details
Free credit	$5 on signup
Llama 3.3 70B price	$0.88/M tokens
Available models	100+ open-source models
Rate limit	60 requests/minute

Setup

from openai import OpenAI

client = OpenAI(
    api_key="your-together-api-key",
    base_url="https://api.together.xyz/v1"
)

response = client.chat.completions.create(
    model="meta-llama/Llama-3.3-70B-Instruct-Turbo",
    messages=[{"role": "user", "content": "Write a FastAPI endpoint for user registration"}],
)
print(response.choices[0].message.content)

Why Use Together AI

Widest selection of open-source models. If you want to test different models (Llama, Qwen, Mistral, DeepSeek), Together has them all on one platform.

3. HuggingFace Inference API

HuggingFace offers free inference for thousands of models hosted on their platform. The free tier is rate-limited but sufficient for development.

Free Tier Details

Feature	Limit
Rate limit	~60 requests/hour (free), higher with Pro
Models	Thousands of open-source models
Dedicated endpoints	Paid only
Serverless inference	Free for popular models

Setup

from huggingface_hub import InferenceClient

client = InferenceClient(
    model="meta-llama/Llama-3.3-70B-Instruct",
    token="hf_xxxxxxxxxxxx"
)

response = client.chat.completions.create(
    messages=[{"role": "user", "content": "Explain async/await in JavaScript"}],
    max_tokens=1024
)
print(response.choices[0].message.content)

Why Use HuggingFace

Access to the largest collection of open-source models. Great for experimentation and trying niche or specialized models that are not available elsewhere.

4. OpenRouter

OpenRouter aggregates models from multiple providers and offers some models for free. It acts as a unified API gateway with OpenAI-compatible endpoints.

Free Models

OpenRouter offers several models at zero cost (community-sponsored):

Model	Context	Status
DeepSeek V3 (free)	128K	Free
Llama 3.3 8B (free)	128K	Free
Mistral 7B (free)	32K	Free
Gemma 2 9B (free)	8K	Free

Free models have lower rate limits and may have queuing during peak times.

Setup

from openai import OpenAI

client = OpenAI(
    api_key="sk-or-xxxxxxxxxxxx",
    base_url="https://openrouter.ai/api/v1"
)

response = client.chat.completions.create(
    model="deepseek/deepseek-chat-v3-0324:free",
    messages=[{"role": "user", "content": "Write a Python decorator for caching"}],
)
print(response.choices[0].message.content)

Why Use OpenRouter

One API key for dozens of providers. Easy model switching. Some genuinely free models. Great fallback when one provider is down.

5. Ollama (Local)

Ollama lets you run open-source LLMs on your own machine. It is completely free, works offline, and keeps all data private.

Setup

# Install Ollama
curl -fsSL https://ollama.com/install.sh | sh

# Download and run a model
ollama pull llama3.3
ollama run llama3.3

Use with OpenAI-Compatible API

Ollama exposes a local API on port 11434:

from openai import OpenAI

client = OpenAI(
    api_key="ollama",  # any string works
    base_url="http://localhost:11434/v1"
)

response = client.chat.completions.create(
    model="llama3.3",
    messages=[{"role": "user", "content": "Explain Docker networking"}],
)
print(response.choices[0].message.content)

Recommended Models for Local Use

Model	Size	RAM Required	Quality
Llama 3.3 8B	4.7 GB	8 GB	Good
Llama 3.3 70B	40 GB	48 GB	Excellent
Qwen 2.5 32B	18 GB	24 GB	Very Good
DeepSeek Coder V2 16B	9 GB	12 GB	Great for code
Mistral Small 22B	13 GB	16 GB	Good
Phi-4 14B	8 GB	12 GB	Good for size

Why Use Ollama

Complete privacy, zero cost, works offline. Essential for developers working with sensitive data or who want unlimited usage without rate limits.

6. Google AI Studio (Gemini)

Google offers a generous free tier for Gemini models through AI Studio, making it one of the best free options for developers.

Free Tier Details

Feature	Limit
Gemini 2.5 Flash	15 requests/minute, 1,500/day
Gemini 2.5 Pro	2 requests/minute, 50/day
Context window	Up to 1M tokens
Price	Free

Setup

import google.generativeai as genai

genai.configure(api_key="your-api-key")
model = genai.GenerativeModel("gemini-2.5-flash")

response = model.generate_content("Write a regex to validate email addresses")
print(response.text)

Why Use Google AI Studio

Gemini 2.5 Flash is one of the best free models available. The 1M token context window is unmatched at this price point.

7. Cerebras

Cerebras provides fast inference powered by their wafer-scale chips. Their free beta tier offers competitive speeds.

Setup

from openai import OpenAI

client = OpenAI(
    api_key="your-cerebras-key",
    base_url="https://api.cerebras.ai/v1"
)

response = client.chat.completions.create(
    model="llama-3.3-70b",
    messages=[{"role": "user", "content": "Explain database indexing strategies"}],
)
print(response.choices[0].message.content)

Why Use Cerebras

Extremely fast inference (competing with Groq). Good free tier for development and prototyping.

8. Cloudflare Workers AI

Cloudflare offers AI inference as part of their Workers platform, with a generous free tier.

Free Tier Details

Feature	Limit
Requests	10,000/day
Models	Llama 3.3, Mistral, and others
Neurons (compute units)	10,000/day
Deployment	Edge (global CDN)

Setup

// Cloudflare Worker
export default {
  async fetch(request, env) {
    const response = await env.AI.run('@cf/meta/llama-3.3-70b-instruct-fp8-fast', {
      messages: [
        { role: 'user', content: 'Explain WebSocket connections' }
      ]
    });
    return new Response(JSON.stringify(response));
  }
};

Why Use Cloudflare Workers AI

Edge deployment (low latency globally), integrated with the Cloudflare ecosystem, and a generous free tier for serverless applications.

How to Choose

Use Case	Recommended
Fastest free inference	Groq or Cerebras
Most model variety	Together AI or OpenRouter
Complete privacy / offline	Ollama
Largest context window (free)	Google AI Studio (Gemini)
Edge deployment	Cloudflare Workers AI
Experimentation with niche models	HuggingFace
Production with free credits	Together AI ($5 credit)
Zero-cost development	Groq + Ollama combo

Universal Python Client

Since most providers support OpenAI-compatible APIs, you can write a universal client that switches between them:

from openai import OpenAI

PROVIDERS = {
    "groq": {
        "base_url": "https://api.groq.com/openai/v1",
        "api_key": "gsk_xxx",
        "model": "llama-3.3-70b-versatile"
    },
    "together": {
        "base_url": "https://api.together.xyz/v1",
        "api_key": "tog_xxx",
        "model": "meta-llama/Llama-3.3-70B-Instruct-Turbo"
    },
    "openrouter": {
        "base_url": "https://openrouter.ai/api/v1",
        "api_key": "sk-or-xxx",
        "model": "deepseek/deepseek-chat-v3-0324:free"
    },
    "ollama": {
        "base_url": "http://localhost:11434/v1",
        "api_key": "ollama",
        "model": "llama3.3"
    },
}

def query(provider: str, prompt: str) -> str:
    config = PROVIDERS[provider]
    client = OpenAI(api_key=config["api_key"], base_url=config["base_url"])
    response = client.chat.completions.create(
        model=config["model"],
        messages=[{"role": "user", "content": prompt}],
    )
    return response.choices[0].message.content

# Use the cheapest available provider
answer = query("groq", "Explain the difference between REST and GraphQL")
print(answer)

Tips for Maximizing Free Tiers

Implement caching. Cache responses for identical or similar queries to reduce API calls.
Use smaller models for simple tasks. An 8B model handles simple formatting, summarization, and extraction well. Save 70B+ models for complex reasoning.
Batch requests. If the API supports it, batch multiple prompts in a single request.
Set up fallbacks. If one provider rate-limits you, automatically fall back to another.
Run a local model for development. Use Ollama locally while developing and switch to a cloud provider for production.
Monitor usage. Track your API calls to avoid surprise charges when free credits run out.

Wrapping Up

The availability of free and open-source LLM APIs in 2026 means every developer can build AI-powered applications without significant upfront costs. Groq and Cerebras offer blazing-fast free inference, Google AI Studio provides massive context windows, and Ollama gives you unlimited local usage. Combine multiple providers for a robust, cost-effective AI infrastructure.

If your application also needs AI-generated media -- images, videos, audio, or talking avatars -- check out Hypereal AI for a unified API with pay-as-you-go pricing and free starter credits.

Try Hypereal AI free -- 35 credits, no credit card required.