Ollama
Get up and running with large language models locally
230K+
GitHub Stars
100+
Models
100%
Free & Open
Overview
Ollama is an open-source tool that makes running large language models locally as simple as a single command. It packages model weights, configurations, and dependencies into a unified system called Modelfiles, letting developers pull and run models like Llama 3, Mistral, Gemma, and dozens more with ollama run llama3. Built on llama.cpp for inference, Ollama provides a REST API compatible with OpenAI's format, making it trivial to swap cloud APIs for local models in existing applications. It runs on macOS, Linux, and Windows with automatic GPU acceleration.
The Verdict
Who Should Use Ollama?
Best For
- Developers prototyping AI apps locally
- Privacy-conscious users and orgs
- Cost-sensitive teams avoiding API fees
- Offline/air-gapped environments
- Quick model experimentation
Not Ideal For
- Production deployments at scale (use vLLM)
- Machines with limited RAM (<8GB)
- Users needing frontier model quality
- Real-time low-latency applications
What's Great
- Dead-simple installation and model management
- OpenAI-compatible REST API out of the box
- Automatic GPU detection and acceleration
- 100% free with no usage limits
- Cross-platform (macOS, Linux, Windows)
- Huge model library with one-command pulls
- Active community and rapid updates
Watch Out For
- Requires significant hardware (8GB+ RAM)
- Local models can't match GPT-4/Claude quality
- No built-in fine-tuning support
- Limited batching for production workloads
- Model downloads can be 4-70GB+ each
Pricing
Open Source
$0
Forever free, MIT licensed
Model Library
Free
100+ models, no signup required
Self-Hosted
Your Hardware
Run anywhere, no cloud costs
View all features & details
Key Features
- One-command model downloads
- OpenAI-compatible REST API
- Modelfile customization
- GPU acceleration (CUDA, Metal, ROCm)
- Multi-model concurrency
- Streaming responses
- System prompt templates
- Import GGUF/Safetensors models
Popular Models
- Llama 3.3 (70B, 8B)
- Mistral / Mixtral
- Gemma 2 (9B, 27B)
- Qwen 2.5 (7B-72B)
- DeepSeek Coder
- Phi-3 / Phi-4
- CodeLlama
- LLaVA (multimodal)
Platforms
- macOS (Apple Silicon, Intel)
- Linux (x86_64, ARM64)
- Windows (native + WSL2)
- Docker container
- Homebrew install
Integrations
- LangChain & LlamaIndex
- Open WebUI
- Continue.dev (VS Code)
- Obsidian plugins
- AnythingLLM
- Jan, LM Studio import
Community & Ecosystem
Model Library
- 100+ curated models
- Multiple quantization levels
- Vision/multimodal support
- Embedding models included
How It Compares
| Feature | Ollama | LM Studio | llama.cpp | vLLM |
|---|---|---|---|---|
| Ease of Use | Very Easy | Easy | Technical | Complex |
| API Server | Built-in | Built-in | Manual | Built-in |
| GUI | CLI only | Full GUI | CLI only | CLI only |
| Model Library | 100+ curated | HuggingFace | Manual | HuggingFace |
| Production Ready | Dev/Hobby | Dev/Hobby | Embedding | Production |
| GPU Support | Auto-detect | Auto-detect | Manual config | Optimized |
| Price | Free | Free | Free | Free |
| Best For | Quick local dev | Non-technical users | Max performance | Production serving |
User Reviews
Loading reviews...