Ollama
AIOpen SourceA lightweight, extensible framework to run, explore, and build with open large language models locally or via cloud.
-(0 Reviews)
Free Available
Starting from Free
Premium plans available
Ollama
AIOpen Source
A lightweight, extensible framework to run, explore, and build with open large language models locally or via cloud.
-(0 Reviews)
Free Available
Starting from Free
Premium plans available
About Ollama
Ollama provides tooling to run and manage large language models on local machines (macOS, Windows, Docker) and to access cloud-hosted models. It combines a lightweight runtime, model discovery, and developer-focused interfaces to enable chat and application-building with open models. Ollama emphasizes local-first operation for privacy and low-latency inference while offering cloud model integration for expanded capabilities. The project is extensible, enabling developers to add and run different open models and integrate them into workflows or applications.
Key Features
Local Model Hosting: Run and serve open large language models on local machines (macOS, Windows) or in containers, enabling offline inference and reduced latency.
Cloud Model Access: Integrate and use cloud-hosted models alongside local models to expand available model choices and scale when needed.
Model Exploration and Catalog: Browse, download, and explore available open models through the Ollama tooling to quickly test options and compare behavior.
Lightweight Extensible Framework: A minimal, extensible runtime and tooling that lets developers add new models and extend capabilities without heavy infrastructure.
Docker Support: Official Docker image and guidelines for running Ollama in containerized environments for reproducible deployments and server setups.
Chat & Build Interfaces: Tools and interfaces aimed at chatting with models and building applications on top of model interactions, streamlining dev workflows.
Cross-Platform Availability: Native installers and support for macOS and Windows plus containerized Linux deployments to accommodate diverse development environments.
Run and manage open-source language models locally
CLI and local HTTP API for inference
Supports macOS, Windows, and Docker-based deployments
Offline inference with no built-in usage fees
Extensible framework for custom models and tooling
Run large language models locally on macOS and Windows
Extensible framework for building and running models on the local machine
Docker image for containerized deployments
Support for CPU-only execution
Model explorer and chat interface to interact with models
Optional cloud model integrations
Open-source repositories and tooling on GitHub
Use Cases
Local development of LLM-powered applications: Developers can run open models locally to develop, test, and iterate on assistants or apps without sending data to third parties.
Private inference for sensitive data: Teams can host models on-premises or on local machines to keep prompts and responses private and under their control.
Model evaluation and comparison: Quickly download and experiment with multiple open models to compare outputs, latency, and resource usage before productionizing.
Containerized deployments: Use the official Docker image to deploy Ollama-backed model serving in reproducible server or CI environments.
Hybrid workflows mixing local and cloud models: Route tasks to local models for privacy or to cloud models for capacity or specialized functionality as needed.
Interactive chat prototypes: Build chat-based prototypes and proof-of-concept assistants using the built-in chat and developer tooling to validate product ideas.
Local development and experimentation with LLMs without cloud costs
On-premise or edge deployments for privacy-sensitive applications
Prototyping and integrating open models into apps via local API
Containerized deployments for reproducible model serving
Local development and testing of language models and applications
Offline or on-premise inference for privacy-sensitive workloads
Containerized deployments using Docker for reproducible environments
Exploration and experimentation with open models and model zoo
Building chat interfaces and custom model-driven tools
Screenshots
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