Download Ollama for Windows
Install the official Ollama app and run open‑source large language models (Llama 3, Mistral, Qwen 2.5, Gemma 2, Phi‑4) locally on your Windows PC — private, fast, and offline.
⬇️ Download Ollama for Windows (Official)
Why run LLMs locally with Ollama?
Keep your data on your machine while getting fast, reliable AI. Ollama makes local models simple for developers and power users alike.
- Easy Windows setup
- One‑command model downloads
- Privacy‑first, offline usage
- Open‑source and community‑driven
Quick start
After installing, open Command Prompt or PowerShell and pull your first model:
Then run it locally:
Developers: head over to the Python section for API usage.
Minimum system requirements
| OS | Windows 10/11 (64‑bit) |
| CPU | Modern multi‑core (Intel i5/AMD Ryzen 5 or better) |
| Memory | 8 GB for smaller models; 16 GB+ recommended for 8B models |
| GPU | NVIDIA CUDA for best acceleration; DirectML support varies by model/driver |
| Disk space | ~5–15 GB per model depending on quantization (e.g., 8B Q4 ≈ ~5–7 GB) |
| License | Open‑source (see upstream project licenses) |
Model sizes and performance vary by parameter count and quantization; GPU VRAM (8 GB+) is recommended for speed, but CPU‑only works for smaller models.
Docs index
Install on Windows
Step‑by‑step setup and first run.
Models Hub
Browse popular models and quick pull commands.
Llama 3
Flagship model variants, tips, and usage.
GPU Acceleration
CUDA and DirectML setup on Windows.
Troubleshooting
Fix common issues and verify your setup.
Python (Developers)
Use the Python client and REST API.
Mistral
Compact, fast models for general tasks.
Update
Keep Ollama and models up to date.
Qwen 2.5
Strong reasoning and multilingual support.
Benchmarks
Measure speed and memory usage properly.
Privacy & Offline
Run fully local and control your data.
Uninstall
Remove the app and clean model files.
Phi‑4 / Gemma 2
Small but capable models for edge use.
FAQ (Extended)
Everything from install to tuning.
Community‑driven guide. Not affiliated with the official Ollama project. The download button links to the official website.