Ollama
Get up and running with large language models.
macOS
Windows preview
Linux
1 | curl -fsSL https://ollama.com/install.sh | sh |
Docker
The official Ollama Docker image ollama/ollama is available on Docker Hub.
Libraries
Quickstart
To run and chat with Llama 3:
1 | ollama run llama3 |
Model library
Ollama supports a list of models available on ollama.com/library
Here are some example models that can be downloaded:
| Model | Parameters | Size | Download |
|---|---|---|---|
| Llama 3 | 8B | 4.7GB | ollama run llama3 |
| Llama 3 | 70B | 40GB | ollama run llama3:70b |
| Phi 3 Mini | 3.8B | 2.3GB | ollama run phi3 |
| Phi 3 Medium | 14B | 7.9GB | ollama run phi3:medium |
| Gemma 2 | 9B | 5.5GB | ollama run gemma2 |
| Gemma 2 | 27B | 16GB | ollama run gemma2:27b |
| Mistral | 7B | 4.1GB | ollama run mistral |
| Moondream 2 | 1.4B | 829MB | ollama run moondream |
| Neural Chat | 7B | 4.1GB | ollama run neural-chat |
| Starling | 7B | 4.1GB | ollama run starling-lm |
| Code Llama | 7B | 3.8GB | ollama run codellama |
| Llama 2 Uncensored | 7B | 3.8GB | ollama run llama2-uncensored |
| LLaVA | 7B | 4.5GB | ollama run llava |
| Solar | 10.7B | 6.1GB | ollama run solar |
[!NOTE]
You should have at least 8 GB of RAM available to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models.
Customize a model
Import from GGUF
Ollama supports importing GGUF models in the Modelfile:
Create a file named
Modelfile, with aFROMinstruction with the local filepath to the model you want to import.1
FROM ./vicuna-33b.Q4_0.gguf
Create the model in Ollama
1
ollama create example -f Modelfile
Run the model
1
ollama run example
Import from PyTorch or Safetensors
See the guide on importing models for more information.
Customize a prompt
Models from the Ollama library can be customized with a prompt. For example, to customize the llama3 model:
1 | ollama pull llama3 |
Create a Modelfile:
1 | FROM llama3 |
Next, create and run the model:
1 | ollama create mario -f ./Modelfile |
For more examples, see the examples directory. For more information on working with a Modelfile, see the Modelfile documentation.
CLI Reference
Create a model
ollama create is used to create a model from a Modelfile.
1 | ollama create mymodel -f ./Modelfile |
Pull a model
1 | ollama pull llama3 |
This command can also be used to update a local model. Only the diff will be pulled.
Remove a model
1 | ollama rm llama3 |
Copy a model
1 | ollama cp llama3 my-model |
Multiline input
For multiline input, you can wrap text with """:
1 | >>> """Hello, |
Multimodal models
1 | >>> What's in this image? /Users/jmorgan/Desktop/smile.png |
Pass the prompt as an argument
1 | $ ollama run llama3 "Summarize this file: $(cat README.md)" |
Show model information
1 | ollama show llama3 |
List models on your computer
1 | ollama list |
Start Ollama
ollama serve is used when you want to start ollama without running the desktop application.
Building
See the developer guide
Running local builds
Next, start the server:
1 | ./ollama serve |
Finally, in a separate shell, run a model:
1 | ./ollama run llama3 |
REST API
Ollama has a REST API for running and managing models.
Generate a response
1 | curl http://localhost:11434/api/generate -d '{ |
Chat with a model
1 | curl http://localhost:11434/api/chat -d '{ |
See the API documentation for all endpoints.
Community Integrations
Web & Desktop
- Open WebUI
- Enchanted (macOS native)
- Hollama
- Lollms-Webui
- LibreChat
- Bionic GPT
- HTML UI
- Saddle
- Chatbot UI
- Chatbot UI v2
- Typescript UI
- Minimalistic React UI for Ollama Models
- Ollamac
- big-AGI
- Cheshire Cat assistant framework
- Amica
- chatd
- Ollama-SwiftUI
- Dify.AI
- MindMac
- NextJS Web Interface for Ollama
- Msty
- Chatbox
- WinForm Ollama Copilot
- NextChat with Get Started Doc
- Alpaca WebUI
- OllamaGUI
- OpenAOE
- Odin Runes
- LLM-X (Progressive Web App)
- AnythingLLM (Docker + MacOs/Windows/Linux native app)
- Ollama Basic Chat: Uses HyperDiv Reactive UI
- Ollama-chats RPG
- QA-Pilot (Chat with Code Repository)
- ChatOllama (Open Source Chatbot based on Ollama with Knowledge Bases)
- CRAG Ollama Chat (Simple Web Search with Corrective RAG)
- RAGFlow (Open-source Retrieval-Augmented Generation engine based on deep document understanding)
- StreamDeploy (LLM Application Scaffold)
- chat (chat web app for teams)
- Lobe Chat with Integrating Doc
- Ollama RAG Chatbot (Local Chat with multiple PDFs using Ollama and RAG)
- BrainSoup (Flexible native client with RAG & multi-agent automation)
- macai (macOS client for Ollama, ChatGPT, and other compatible API back-ends)
- Olpaka (User-friendly Flutter Web App for Ollama)
- OllamaSpring (Ollama Client for macOS)
- LLocal.in (Easy to use Electron Desktop Client for Ollama)
- Ollama with Google Mesop (Mesop Chat Client implementation with Ollama)
- Kerlig AI (AI writing assistant for macOS)
- AI Studio
- Sidellama (browser-based LLM client)
- LLMStack (No-code multi-agent framework to build LLM agents and workflows)
Terminal
- oterm
- Ellama Emacs client
- Emacs client
- gen.nvim
- ollama.nvim
- ollero.nvim
- ollama-chat.nvim
- ogpt.nvim
- gptel Emacs client
- Oatmeal
- cmdh
- ooo
- shell-pilot
- tenere
- llm-ollama for Datasette’s LLM CLI.
- typechat-cli
- ShellOracle
- tlm
- podman-ollama
- gollama
Database
- MindsDB (Connects Ollama models with nearly 200 data platforms and apps)
- chromem-go with example
Package managers
Libraries
- LangChain and LangChain.js with example
- LangChainGo with example
- LangChain4j with example
- LangChainRust with example
- LlamaIndex
- LiteLLM
- OllamaSharp for .NET
- Ollama for Ruby
- Ollama-rs for Rust
- Ollama-hpp for C++
- Ollama4j for Java
- ModelFusion Typescript Library
- OllamaKit for Swift
- Ollama for Dart
- Ollama for Laravel
- LangChainDart
- Semantic Kernel - Python
- Haystack
- Elixir LangChain
- Ollama for R - rollama
- Ollama for R - ollama-r
- Ollama-ex for Elixir
- Ollama Connector for SAP ABAP
- Testcontainers
- Portkey
- PromptingTools.jl with an example
- LlamaScript
Mobile
Extensions & Plugins
- Raycast extension
- Discollama (Discord bot inside the Ollama discord channel)
- Continue
- Obsidian Ollama plugin
- Logseq Ollama plugin
- NotesOllama (Apple Notes Ollama plugin)
- Dagger Chatbot
- Discord AI Bot
- Ollama Telegram Bot
- Hass Ollama Conversation
- Rivet plugin
- Obsidian BMO Chatbot plugin
- Cliobot (Telegram bot with Ollama support)
- Copilot for Obsidian plugin
- Obsidian Local GPT plugin
- Open Interpreter
- Llama Coder (Copilot alternative using Ollama)
- Ollama Copilot (Proxy that allows you to use ollama as a copilot like Github copilot)
- twinny (Copilot and Copilot chat alternative using Ollama)
- Wingman-AI (Copilot code and chat alternative using Ollama and HuggingFace)
- Page Assist (Chrome Extension)
- AI Telegram Bot (Telegram bot using Ollama in backend)
- AI ST Completion (Sublime Text 4 AI assistant plugin with Ollama support)
- Discord-Ollama Chat Bot (Generalized TypeScript Discord Bot w/ Tuning Documentation)
- Discord AI chat/moderation bot Chat/moderation bot written in python. Uses Ollama to create personalities.
- Headless Ollama (Scripts to automatically install ollama client & models on any OS for apps that depends on ollama server)
Supported backends
- llama.cpp project founded by Georgi Gerganov.