OllamaFreeAPI

March 24, 2026 ยท View on GitHub

PyPI Version Python Versions License Free API

Unlock AI Innovation for Free

Access the world's best open language models in one place!

OllamaFreeAPI provides free access to leading open-source LLMs including:

  • ๐Ÿฆ™ LLaMA (Meta)
  • ๐ŸŒช๏ธ Mistral (Mistral AI)
  • ๐Ÿ” DeepSeek (DeepSeek)
  • ๐Ÿฆ„ Qwen (Alibaba Cloud)

No payments. No credit cards. Just pure AI power at your fingertips.

# Install or upgrade to the latest version
pip install ollamafreeapi --upgrade

๐Ÿ“š Documentation

Why Choose OllamaFreeAPI?

FeatureOthersOllamaFreeAPI
Free AccessโŒ Limited trialsโœ… Always free
Model Variety3-5 modelsVerified endpoints only
ReliabilityHighly variableValidated active models
Ease of UseComplex setupZero-config
Community SupportPaid onlyFree & active

๐Ÿ“Š Project Statistics

Here are some key statistics about the current state of OllamaFreeAPI:

  • Active Models: 16 (Ready to use and tested)
  • Model Families: 3 (gemma, llama, qwen)
  • Endpoints: 6 highly reliable server nodes

๐Ÿš€ Quick Start

Streaming Example

from ollamafreeapi import OllamaFreeAPI

client = OllamaFreeAPI()

# Stream responses in real-time
for chunk in client.stream_chat('What is quantum computing?', model='llama3.2:3b'):
    print(chunk, end='', flush=True)

Non-Streaming Example

from ollamafreeapi import OllamaFreeAPI

client = OllamaFreeAPI()

# Get instant responses
response = client.chat(
    model="gpt-oss:20b",
    prompt="Explain neural networks like I'm five",
    temperature=0.7
)
print(response)
  • llama3.2:3b - Meta's efficient 3.2B parameter model
  • deepseek-r1:latest - Strong reasoning capabilities built on Qwen
  • gpt-oss:20b - Powerful Gemma-based 20B completion model
  • mistral:latest - High-performance baseline Mistral model

Specialized Models

  • mistral-nemo:custom - 12.2B open weights language model
  • bakllava:latest - Vision and language model
  • smollm2:135m - Extremely lightweight assistant

๐ŸŒ Global Infrastructure

Our free API is powered by distributed community nodes:

  • Fast response times
  • Automatic load balancing and server selection
  • Real-time availability checks

๐Ÿ“„ API Reference

Core Methods

# List available models
api.list_models()  

# Get model details
api.get_model_info("mistral:latest")  

# Generate text
api.chat(model="llama3.2:3b", prompt="Your message")

# Stream responses
for chunk in api.stream_chat(prompt="Hello!", model="llama3:latest"):
    print(chunk, end='')

Advanced Features

# Check server locations
api.get_model_servers("deepseek-r1:latest")

# Generate raw API request
api.generate_api_request(model="llama3.2:3b", prompt="Hello")

# Get random model parameters (useful for LangChain integration)
api.get_llm_params()

๐Ÿค Contributing

We welcome contributions! Please see our Contributing Guide for details.

๐Ÿ“„ License

Open-source MIT license - View License