What hardware do I need to run Ollama?

Minimum: 8GB RAM for 7B models. Recommended: 16GB RAM for 13B models, 32GB+ for 70B models. Ollama runs on Apple Silicon (M1/M2/M3) natively and supports NVIDIA/AMD GPUs on Windows/Linux. CPU-only is also supported but slower.

Yes. Ollama is completely free and open source (MIT license). All models available in the Ollama library are also free to download and use locally.

What models does Ollama support?

Ollama supports 100+ models including Llama 3 (Meta), Mistral, Gemma (Google), Phi-3 (Microsoft), CodeLlama, Vicuna, Orca, and many more. New models are added regularly via the Ollama model library at ollama.com/library.

Does Ollama have an API?

Yes. Ollama exposes a REST API on port 11434 that is compatible with the OpenAI API format. This means any tool that works with the OpenAI API (LangChain, Open WebUI, etc.) can use Ollama as a local backend.

Ollama Review 2026 | Run LLMs Locally on Your Machine

License

MIT

Free & open source

Models

100+

Llama, Mistral, Gemma, Phi

Min RAM

8 GB

For 7B parameter models

Platforms

Mac, Win, Linux

Apple Silicon + NVIDIA GPU

What Is Ollama?

Ollama is an open-source tool that makes running large language models on your own machine as easy as running a Docker container. Launched in 2023, it quickly became the go-to solution for developers who want the power of ChatGPT-level AI without sending data to the cloud.

Under the hood, Ollama uses llama.cpp for fast CPU and GPU inference, GGUF model format for efficient quantization, and a clean CLI + REST API interface. It supports Apple Silicon natively with Metal GPU acceleration, giving M1/M2/M3 Mac users exceptional performance.

Quick Start

💡 Ollama installs as a native app on Mac/Windows or as a Linux service.

Download from ollama.com for your OS, or install via curl on Linux.
Pull a model: ollama pull llama3 (downloads ~4GB for 8B model)
Start chatting: ollama run llama3
Access the API: curl http://localhost:11434/api/generate
Pair with Open WebUI for a ChatGPT-like browser interface.

Popular Models

🦙
Llama 3.3 (70B) — Meta's best open model. Comparable to GPT-4o on many benchmarks. Requires 40GB+ RAM.
⚡
Llama 3.2 (3B / 1B) — Ultra-fast small models. Runs on any modern laptop. Great for quick tasks and edge deployment.
🔷
Mistral 7B / Mixtral — French AI startup's models. Excellent instruction-following and coding at small size.
💎
Gemma 2 (Google) — Google's open model family. Gemma2 9B outperforms models twice its size on many benchmarks.
🔬
Phi-3 (Microsoft) — Small but mighty. Phi-3 mini (3.8B) matches much larger models in reasoning tasks.
💻
CodeLlama / DeepSeek Coder — Specialized coding models. Better than Llama at code generation tasks.

Use Cases

Privacy-Sensitive Applications

Any application where data cannot leave the company: medical records analysis, legal document review, internal code review, or enterprise knowledge base queries. Ollama enables enterprise-grade AI with zero data egress.

Development & Prototyping

Develop and test AI applications locally before deploying to production. The OpenAI-compatible API means you can swap between Ollama (development) and OpenAI (production) with a single URL change.

Offline AI

Field work, air-gapped environments, or areas with unreliable internet. Ollama works fully offline once models are downloaded.

Pros & Cons

Pros

100% free and open source
Full privacy: data never leaves your machine
OpenAI-compatible API
Excellent Apple Silicon performance
100+ models available with one command
Active development, frequent updates

Cons

Hardware-limited: needs 8GB+ RAM
Slower than cloud APIs on CPU
Smaller models = lower quality than GPT-4o
No built-in web UI (use Open WebUI)
Model downloads are large (4-40GB)

Frequently Asked Questions

What hardware do I need? ▼

Minimum 8GB RAM for 7B models. Recommended: 16GB for 13B models, 32GB+ for 70B models. Apple M1/M2/M3 chips are ideal. NVIDIA/AMD GPUs are supported on Windows and Linux for much faster inference.

Is Ollama free? ▼

Yes, completely free and MIT licensed. All models in the Ollama library are also free to download and use.

How does Ollama compare to OpenAI? ▼

OpenAI's models (GPT-4o) are generally more capable than local models, especially for complex reasoning. But Ollama wins on privacy, cost (free), and latency for simple tasks. Many teams use Ollama for development and OpenAI for production.

Can I use Ollama with LangChain? ▼

Yes. LangChain has native Ollama integration via the `langchain-ollama` package. Since Ollama also exposes an OpenAI-compatible API, any LangChain code using the OpenAI provider works with Ollama by changing the base URL to http://localhost:11434/v1.

Can Ollama run vision models? ▼

Yes. Ollama supports LLaVA, Moondream, and other multimodal models. Run `ollama run llava` and pass image paths in your prompts for local image understanding.

Ollama – Run LLMs Locally, No Cloud Required