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* bench: add prompt calibration, context size flag, and NumCtx reporting Add --num-ctx flag to set context size, and report NumCtx in model info header. Calibrate tokens-per-word ratio during warmup using actual tokenization metrics from the model, replacing the fixed 1.3 heuristic. This produces more accurate prompt token counts for --prompt-tokens. Also add fetchContextLength() to query running model context via /api/ps. * integration: improve vision test robustness and add thinking tests Add skipIfNoVisionOverride() to skip vision tests when OLLAMA_TEST_MODEL is set to a non-vision model. Add Think:false to context exhaustion test to prevent thinking models from using all context before the test can measure it. Add third test image (ollama homepage) and replace OCR test with ImageDescription test using it. Relax match strings for broader model compatibility. Add TestThinkingEnabled and TestThinkingSuppressed to verify thinking output and channel tag handling. * gemma4: add Gemma 4 GGML model support Add full Gemma 4 model family support (E2B, E4B, 26B MoE, 31B Dense) for the GGML backend including text, vision, converter, parser, and renderer. Text model features: - Sliding window + full attention with per-layer patterns - KV sharing across layers with donor map - Per-layer embeddings (PLE) with learned projections - MoE routing with RMSNorm + learned scale - Proportional RoPE with freq_factors for global attention - Final logit softcapping Vision model features: - SigLIP vision encoder with 2D RoPE - ClippableLinear with input/output clamping via packed v.clamp_data - Adaptive average pooling with nMerge kernel - Multi-modal projection with unweighted RMSNorm Converter: - Safetensors to GGUF with vision tensor renaming - Fused MoE gate_up_proj splitting - Vision patch embedding reshape (HF to Conv2D layout) - Packed clamp data tensor for ClippableLinear bounds - Proportional RoPE freq_factors generation Also includes: - BackendGet() on ml.Tensor for reading weight tensor data - Q6_K CUDA get_rows kernel support - MoE-aware ffn_down quantization layer counting - Gemma4 parser with tool calling and thinking support - Gemma4 renderer with structured tool format - Architecture-based auto-detection of renderer/parser/stop tokens - Integration test gemma4 model list additions * gemma4: add audio support with USM conformer encoder Add audio encoding for Gemma 4 using the USM conformer architecture: - Converter: audio tensor mapping, SSCP/conformer/embedder name replacements, softplus repacker for per_dim_scale, F32 enforcement for conv weights - GGML backend: Conv1DDW and PadExt tensor ops - Audio encoder: SSCP Conv2D, 12 conformer blocks (FFW + block-local attention with relative position embeddings + LightConv1d + FFW), output projection, audio-to-text embedding projector - Audio preprocessing: WAV decode, mel spectrogram, FFT (pure Go) - Model wiring: WAV detection, audio token handling, unified PostTokenize Correctly transcribes "why is the sky blue" from test audio. * integration: add gemma4 audio tests including OpenAI API coverage Test audio transcription and response via the Ollama native API, plus two new tests exercising the OpenAI-compatible endpoints: - /v1/audio/transcriptions (multipart form upload) - /v1/chat/completions with input_audio content type All tests use capability checks and skip models without audio support. * gemma4: add OpenAI audio API support and capability detection - Add CapabilityAudio and detect from audio.block_count in GGUF - Add /v1/audio/transcriptions endpoint with TranscriptionMiddleware - Add input_audio content type support in /v1/chat/completions - Add TranscriptionRequest/Response types in openai package * gemma4: add audio input support for run command - /audio toggle in interactive mode for voice chat - Platform-specific microphone recording (AVFoundation on macOS, PulseAudio/ALSA on Linux, WASAPI on Windows) - Space to start/stop recording, automatic chunking for long audio * gemma4: add transcribe command (ollama transcribe MODEL) - Interactive mode with readline prompt and slash commands - Non-interactive mode for piped audio or record-until-Ctrl+C - Chunked streaming transcription for long recordings - Word-wrapped output matching run command style * gemma4: add parser, renderer, and integration test plumbing * gemma4: fix renderer to emit BOS token * gemma4: add OpenAI audio transcription API and input_audio support * gemma4: update converter for new weight drop naming * gemma4: add per_expert_scale to MoE router and fix moe_intermediate_size config * gemma4: rewrite renderer to match HF Jinja2 template exactly Fix 8 bugs found by building 55 reference tests verified against the HF Jinja2 chat template (VERIFY_JINJA2=1 shells out to Python): - Tool responses use separate <|turn>tool turns (not inline tags) - Tool calls emitted before content in assistant messages - Thinking content stripped from assistant history (strip_thinking) - User, tool, and system content trimmed (template does | trim) - Empty system message still emits system turn (check role, not content) - Nested object properties rendered recursively with required field - Array items specification rendered for array-type properties - OBJECT/ARRAY type-specific rendering comma logic matches template Also adds Required field to api.ToolProperty for nested object schemas, replaces old gemma4_test.go with comprehensive gemma4_reference_test.go, and commits the Jinja2 template as testdata for verification. * gemma4: fix MoE fused gate_up split and multiline tool-call arg parsing - Text MoE: split `ffn_gate_up_exps` into contiguous `[gate|up]` halves instead of stride-2 slices. - Parser: escape control characters in `<|"|>...<|"|>` string literals when converting tool-call args to JSON. - Fixes warnings like `invalid character '\n' in string literal` for multiline tool arguments. - Add Gemma4 parser regressions for multiline tool-call args and `gemma4ArgsToJSON`. * cmd: simplify audio input to dropped file attachments * gemma4: use full SWA memory for better cache reuse * gemma4: initialize clamps after backend load * convert: align gemma4 audio tensor renames with llama.cpp * Remove redundant comments in gemma4 vision model * Format Gemma4 MoE block field alignment * use 4096 kvcache.NewSWAMemCache * convert: support new Gemma4 audio_tower tensor naming (#15221) Co-authored-by: jmorganca <jmorganca@gmail.com> * fix integration test defaults for audio * review comments and lint fixes * remove unused audio/video files --------- Co-authored-by: jmorganca <jmorganca@gmail.com> |
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Ollama
Start building with open models.
Download
macOS
curl -fsSL https://ollama.com/install.sh | sh
Windows
irm https://ollama.com/install.ps1 | iex
Linux
curl -fsSL https://ollama.com/install.sh | sh
Docker
The official Ollama Docker image ollama/ollama is available on Docker Hub.
Libraries
Community
Get started
ollama
You'll be prompted to run a model or connect Ollama to your existing agents or applications such as claude, codex, openclaw and more.
Coding
To launch a specific integration:
ollama launch claude
Supported integrations include Claude Code, Codex, Droid, and OpenCode.
AI assistant
Use OpenClaw to turn Ollama into a personal AI assistant across WhatsApp, Telegram, Slack, Discord, and more:
ollama launch openclaw
Chat with a model
Run and chat with Gemma 3:
ollama run gemma3
See ollama.com/library for the full list.
See the quickstart guide for more details.
REST API
Ollama has a REST API for running and managing models.
curl http://localhost:11434/api/chat -d '{
"model": "gemma3",
"messages": [{
"role": "user",
"content": "Why is the sky blue?"
}],
"stream": false
}'
See the API documentation for all endpoints.
Python
pip install ollama
from ollama import chat
response = chat(model='gemma3', messages=[
{
'role': 'user',
'content': 'Why is the sky blue?',
},
])
print(response.message.content)
JavaScript
npm i ollama
import ollama from "ollama";
const response = await ollama.chat({
model: "gemma3",
messages: [{ role: "user", content: "Why is the sky blue?" }],
});
console.log(response.message.content);
Supported backends
- llama.cpp project founded by Georgi Gerganov.
Documentation
Community Integrations
Want to add your project? Open a pull request.
Chat Interfaces
Web
- Open WebUI - Extensible, self-hosted AI interface
- Onyx - Connected AI workspace
- LibreChat - Enhanced ChatGPT clone with multi-provider support
- Lobe Chat - Modern chat framework with plugin ecosystem (docs)
- NextChat - Cross-platform ChatGPT UI (docs)
- Perplexica - AI-powered search engine, open-source Perplexity alternative
- big-AGI - AI suite for professionals
- Lollms WebUI - Multi-model web interface
- ChatOllama - Chatbot with knowledge bases
- Bionic GPT - On-premise AI platform
- Chatbot UI - ChatGPT-style web interface
- Hollama - Minimal web interface
- Chatbox - Desktop and web AI client
- chat - Chat web app for teams
- Ollama RAG Chatbot - Chat with multiple PDFs using RAG
- Tkinter-based client - Python desktop client
Desktop
- Dify.AI - LLM app development platform
- AnythingLLM - All-in-one AI app for Mac, Windows, and Linux
- Maid - Cross-platform mobile and desktop client
- Witsy - AI desktop app for Mac, Windows, and Linux
- Cherry Studio - Multi-provider desktop client
- Ollama App - Multi-platform client for desktop and mobile
- PyGPT - AI desktop assistant for Linux, Windows, and Mac
- Alpaca - GTK4 client for Linux and macOS
- SwiftChat - Cross-platform including iOS, Android, and Apple Vision Pro
- Enchanted - Native macOS and iOS client
- RWKV-Runner - Multi-model desktop runner
- Ollama Grid Search - Evaluate and compare models
- macai - macOS client for Ollama and ChatGPT
- AI Studio - Multi-provider desktop IDE
- Reins - Parameter tuning and reasoning model support
- ConfiChat - Privacy-focused with optional encryption
- LLocal.in - Electron desktop client
- MindMac - AI chat client for Mac
- Msty - Multi-model desktop client
- BoltAI for Mac - AI chat client for Mac
- IntelliBar - AI-powered assistant for macOS
- Kerlig AI - AI writing assistant for macOS
- Hillnote - Markdown-first AI workspace
- Perfect Memory AI - Productivity AI personalized by screen and meeting history
Mobile
- Ollama Android Chat - One-click Ollama on Android
SwiftChat, Enchanted, Maid, Ollama App, Reins, and ConfiChat listed above also support mobile platforms.
Code Editors & Development
- Cline - VS Code extension for multi-file/whole-repo coding
- Continue - Open-source AI code assistant for any IDE
- Void - Open source AI code editor, Cursor alternative
- Copilot for Obsidian - AI assistant for Obsidian
- twinny - Copilot and Copilot chat alternative
- gptel Emacs client - LLM client for Emacs
- Ollama Copilot - Use Ollama as GitHub Copilot
- Obsidian Local GPT - Local AI for Obsidian
- Ellama Emacs client - LLM tool for Emacs
- orbiton - Config-free text editor with Ollama tab completion
- AI ST Completion - Sublime Text 4 AI assistant
- VT Code - Rust-based terminal coding agent with Tree-sitter
- QodeAssist - AI coding assistant for Qt Creator
- AI Toolkit for VS Code - Microsoft-official VS Code extension
- Open Interpreter - Natural language interface for computers
Libraries & SDKs
- LiteLLM - Unified API for 100+ LLM providers
- Semantic Kernel - Microsoft AI orchestration SDK
- LangChain4j - Java LangChain (example)
- LangChainGo - Go LangChain (example)
- Spring AI - Spring framework AI support (docs)
- LangChain and LangChain.js with example
- Ollama for Ruby - Ruby LLM library
- any-llm - Unified LLM interface by Mozilla
- OllamaSharp for .NET - .NET SDK
- LangChainRust - Rust LangChain (example)
- Agents-Flex for Java - Java agent framework (example)
- Elixir LangChain - Elixir LangChain
- Ollama-rs for Rust - Rust SDK
- LangChain for .NET - .NET LangChain (example)
- chromem-go - Go vector database with Ollama embeddings (example)
- LangChainDart - Dart LangChain
- LlmTornado - Unified C# interface for multiple inference APIs
- Ollama4j for Java - Java SDK
- Ollama for Laravel - Laravel integration
- Ollama for Swift - Swift SDK
- LlamaIndex and LlamaIndexTS - Data framework for LLM apps
- Haystack - AI pipeline framework
- Firebase Genkit - Google AI framework
- Ollama-hpp for C++ - C++ SDK
- PromptingTools.jl - Julia LLM toolkit (example)
- Ollama for R - rollama - R SDK
- Portkey - AI gateway
- Testcontainers - Container-based testing
- LLPhant - PHP AI framework
Frameworks & Agents
- AutoGPT - Autonomous AI agent platform
- crewAI - Multi-agent orchestration framework
- Strands Agents - Model-driven agent building by AWS
- Cheshire Cat - AI assistant framework
- any-agent - Unified agent framework interface by Mozilla
- Stakpak - Open source DevOps agent
- Hexabot - Conversational AI builder
- Neuro SAN - Multi-agent orchestration (docs)
RAG & Knowledge Bases
- RAGFlow - RAG engine based on deep document understanding
- R2R - Open-source RAG engine
- MaxKB - Ready-to-use RAG chatbot
- Minima - On-premises or fully local RAG
- Chipper - AI interface with Haystack RAG
- ARGO - RAG and deep research on Mac/Windows/Linux
- Archyve - RAG-enabling document library
- Casibase - AI knowledge base with RAG and SSO
- BrainSoup - Native client with RAG and multi-agent automation
Bots & Messaging
- LangBot - Multi-platform messaging bots with agents and RAG
- AstrBot - Multi-platform chatbot with RAG and plugins
- Discord-Ollama Chat Bot - TypeScript Discord bot
- Ollama Telegram Bot - Telegram bot
- LLM Telegram Bot - Telegram bot for roleplay
Terminal & CLI
- aichat - All-in-one LLM CLI with Shell Assistant, RAG, and AI tools
- oterm - Terminal client for Ollama
- gollama - Go-based model manager for Ollama
- tlm - Local shell copilot
- tenere - TUI for LLMs
- ParLlama - TUI for Ollama
- llm-ollama - Plugin for Datasette's LLM CLI
- ShellOracle - Shell command suggestions
- LLM-X - Progressive web app for LLMs
- cmdh - Natural language to shell commands
- VT - Minimal multimodal AI chat app
Productivity & Apps
- AppFlowy - AI collaborative workspace, self-hostable Notion alternative
- Screenpipe - 24/7 screen and mic recording with AI-powered search
- Vibe - Transcribe and analyze meetings
- Page Assist - Chrome extension for AI-powered browsing
- NativeMind - Private, on-device browser AI assistant
- Ollama Fortress - Security proxy for Ollama
- 1Panel - Web-based Linux server management
- Writeopia - Text editor with Ollama integration
- QA-Pilot - GitHub code repository understanding
- Raycast extension - Ollama in Raycast
- Painting Droid - Painting app with AI integrations
- Serene Pub - AI roleplaying app
- Mayan EDMS - Document management with Ollama workflows
- TagSpaces - File management with AI tagging
Observability & Monitoring
- Opik - Debug, evaluate, and monitor LLM applications
- OpenLIT - OpenTelemetry-native monitoring for Ollama and GPUs
- Lunary - LLM observability with analytics and PII masking
- Langfuse - Open source LLM observability
- HoneyHive - AI observability and evaluation for agents
- MLflow Tracing - Open source LLM observability
Database & Embeddings
- pgai - PostgreSQL as a vector database (guide)
- MindsDB - Connect Ollama with 200+ data platforms
- chromem-go - Embeddable vector database for Go (example)
- Kangaroo - AI-powered SQL client
Infrastructure & Deployment
Cloud
- Google Cloud
- Fly.io
- Koyeb
- Harbor - Containerized LLM toolkit with Ollama as default backend