Ollama

Run Large Language Models Locally

The simplest way to run open-source LLMs on your own hardware. GPU acceleration, 100+ models, and complete privacy — all with a single command.

OllamaLocal LLM Platform🏠Local LLMs📚Model Libra...GPU Acceler...🔌OpenAI API📊Quantization🐳Docker Depl...📝Modelfile👁️Vision Mode...🧮Embeddings💻CLI Interfa...🌊Streaming🔒Privacy Fir...

Click on any feature node to explore Ollama's capabilities

Core Capabilities

📚

Model Library

  • 100+ pre-built models available
  • Llama 3.3, DeepSeek-R1, Qwen3-235B
  • Mistral, Gemma 2, GLM-4 series
  • Vision models (LLaVA, Llama Vision)
  • One-command pull & run

GPU Acceleration

  • NVIDIA CUDA support
  • AMD ROCm acceleration
  • Apple Metal API
  • Multi-GPU distribution
  • Automatic hardware detection
🔌

OpenAI-Compatible API

  • Drop-in replacement endpoints
  • Chat completions API
  • Embeddings generation
  • Streaming responses
  • Works with existing tools
📊

Memory Optimization

  • GGUF quantization format
  • Q4_K_M, FP8 for efficiency
  • 75% size reduction, minimal loss
  • Partial GPU offloading
  • Run 70B+ on 16GB VRAM
🚀

Deployment Options

  • Native Mac/Linux/Windows
  • Official Docker images
  • Kubernetes ready
  • Background service mode
  • Production scaling
💻

Developer Experience

  • Simple CLI interface
  • Modelfile customization
  • REST API access
  • Python, JavaScript SDKs
  • LangChain integration

Why We Deploy Ollama

🔒

Complete Data Privacy

Everything runs locally on your machine. Your prompts, documents, and outputs never leave your infrastructure — essential for sensitive business data.

💵

Zero Per-Token Costs

No API fees, no rate limits, no surprise bills. Run as many queries as your hardware allows. One-time hardware investment instead of ongoing expenses.

📡

Offline Operation

Works completely offline once models are downloaded. Perfect for air-gapped environments, remote sites, or unreliable internet connections.

🔄

Model Flexibility

Switch between models instantly. Test Llama, Mistral, and DeepSeek side-by-side. Use the right model for each task without vendor lock-in.

🧩

Easy Integration

OpenAI-compatible API means existing applications often work without changes. LangChain, CrewAI, and other frameworks integrate seamlessly.

🚀

Active Development

Regular updates with new models, performance improvements, and features. Strong community support and extensive documentation.

Popular Models

Ollama's library includes models for every use case — from quick tasks on laptops to enterprise workloads on GPUs.

Qwen3-235B
Top coding/math, 12x context extension
24GB (4-bit)
DeepSeek-R1
Chain-of-thought reasoning, MIT licensed
16GB (14B)
Llama 3.3 70B
Meta's flagship, state-of-art performance
40GB
GLM-4
Optimized for agentic tasks and coding
Various
Mistral Small 3
Best-in-class efficiency under 70B
14GB
Gemma 2
Google's efficient open-weight model
5-18GB
LLaVA
Vision-language model for image analysis
8-26GB
nomic-embed-text
High-quality embeddings for RAG
274MB

Get Started in Seconds

# Install Ollama
curl -fsSL https://ollama.com/install.sh | sh
# Run a model
ollama run llama3.3
# API is automatically available at
curl http://localhost:11434/api/generate -d '{"model":"llama3.3","prompt":"Hello"}'

Ready for Local AI?

We can help you evaluate, deploy, and integrate Ollama into your organization's AI infrastructure.