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published AI Powered

Ollama API

The Ollama API offers developers a way to run over 100 large language models locally with no dependencies on cloud services, ensuring complete data privacy.

Developed by Ollama

99.90%Uptime
50msLatency
3.5kStars
No AuthAuth
NoCredit Card
RESTStyle
v1Version

Reference

API Endpoints

Endpoints

Available routes, request structures, and code examples.

Generates text using local language models

Endpoint URL
http://localhost:11434/api/generate
Code Example
curl -X POST 'http://localhost:11434/api/generate'
Request Payload
{
  "model": "llama2",
  "prompt": "Explain quantum computing basics",
  "stream": false
}
Expected Response
{
  "done": true,
  "model": "llama2",
  "response": "Quantum computing uses qubits...",
  "created_at": "2023-07-18T16:00:00Z"
}
Version:v1

Integration

Quick Start

cURL ExampleREST
curl -X GET "http://localhost:11434/api/v1/run"

Docs

Technical Documentation

What this API does

The Ollama API enables developers to execute large language models like Llama 2, Mistral, and Gemma directly on their local machines. This service ensures total data privacy and removes the necessity for cloud-based solutions. The API provides a RESTful interface, supporting JSON responses for straightforward integration into various applications.

How it works

To use the Ollama API, developers send HTTP requests to interact with the models. The API supports features such as real-time response streaming and adjustable context length for tailored outputs. Example endpoints include /api/v1/run, allowing execution of various models in real time.

Authentication

No authentication is required to use the Ollama API. This makes it easy for developers to start using the service immediately without the need for API keys or tokens.

Example usage

  • /api/v1/run - Executes a specified model and returns the output in JSON format.
  • /api/v1/models - Retrieves a list of available language models.

Limits

No specific rate limits are documented for the Ollama API. Developers can make requests freely without concerns of hitting a limit.

Ideal use cases

  • Local AI-powered application development for privacy-sensitive projects.
  • Prototyping and deploying AI applications in controlled environments.
  • Real-time data processing with large language models.

Examples

Real-World Applications

  • Local AI model prototyping and testing
  • Privacy-focused conversational AI
  • On-premise NLP tasks without cloud dependency
  • Custom AI-powered chatbots for desktop apps
  • Secure AI integration in sensitive environments

Evaluation

Advantages & Limitations

Advantages
  • ✓ Complete data privacy with local model execution
  • ✓ Supports over 100 models including popular LLMs
  • ✓ No authentication needed, easy setup
  • ✓ Open-source and free to use
Limitations
  • ✗ Requires local machine resources to run models
  • ✗ No cloud-hosted option for scalability
  • ✗ Limited official SDK support
  • ✗ Documentation could be more extensive for beginners

Support

Frequently Asked Questions

Important Notice

Verify Before You Decide

Last verified · Apr 30, 2026

The details on this page — including pricing, features, and availability — are based on our last review and may not reflect the provider's current offering. Providers update their products frequently, sometimes without prior notice.

What may have changed

Pricing Plans
Features & Limits
Availability
Terms & Policies

Always visit the official provider website to confirm the latest pricing, terms, and feature availability before subscribing or integrating.

Check official site

External Resources

Documentation Official Website Pricing Details Postman Collection

API Specifications

v1
Pricing Model
Free and open-source
Credit Card
Not Required
Response Formats
JSON
Supported Languages
6 Languages
SDK Support
Python, JavaScript
Rate Limit

Unlimited (Local Use)

Time to Hello World

Under 15 minutes for local setup

Free Tier

Unlimited usage with local models; no restrictions or credits needed

Best For

Developers needing private, fast, and local LLM access

Not Ideal For

Teams needing cloud-scaled AI services or multi-user SaaS

Tags

#offline#mistral#llama#ollama#privacy#local-ai#llm#ai#open-source

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