LocalAI vs Ollama
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
Open-source engine that runs AI models (text, vision, voice, image, video) locally behind an OpenAI-style API.
Open source · MIT
Runs open AI models like Gemma, Qwen and DeepSeek on your own machine or in the cloud.
Our verdict
LocalAI is a self-hosted server that runs many kinds of AI models (text, vision, voice, image, video) behind an OpenAI-compatible API, aimed at developers and teams who want that on their own hardware and are willing to deal with more setup. Ollama is a simpler tool for downloading and running open language models with a few terminal commands, aimed at people who want to chat with open models or build small apps quickly. They overlap on local model serving, but LocalAI is broader and more configurable, while Ollama is easier to start with and centres on language models.
Pick LocalAI if you need one self-hosted API that handles text, voice and image models and must match OpenAI, Anthropic or ElevenLabs endpoints in your existing code.
Pick Ollama if you want the quickest way to run open language models locally from a terminal and call them from your own apps or a coding assistant.
| Key difference | LocalAI | Ollama |
|---|---|---|
| Setup | Intermediate; configuration is complex; run with Docker | Beginner; simple install and run commands on macOS, Windows, Linux, Docker |
| Model types | Text, vision, voice, image and video models | Open language models such as Gemma, Qwen and DeepSeek |
| API compatibility | OpenAI, Anthropic and ElevenLabs compatible API | Documented REST API plus official Python and JavaScript libraries |
| Hardware | Supports NVIDIA, AMD, Intel, Apple Silicon and CPU-only machines | Runs on macOS, Windows and Linux; README gives no hardware requirements |
| Best at | Privacy-focused, multi-model serving for developers and teams | Easy private chat with open models and quick integration with tools |
Written with AI from both products' catalogue entries · updated 2026-10-29
Who each one is for
Choose LocalAI if you need…
- Developers who want an OpenAI-compatible endpoint running on their own machines or servers
- Teams that need privacy and want data to stay inside their infrastructure
- People experimenting with several model types (text, voice, image) behind one API
- Users with mixed hardware, such as NVIDIA, AMD, Intel, Apple Silicon or CPU-only machines
Choose Ollama if you need…
- Developers who want a local model API for their own apps
- People who want to chat with open models without sending prompts to a hosted service
- Users who want to connect a coding assistant to a local or self-chosen model
- Students experimenting with different open models from a terminal
Side-by-side
| LocalAI | Ollama | |
|---|---|---|
| Type | App | App |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 50.1k | 186k |
| Setup difficulty | Intermediate | Beginner |
| How you get it | Run with Docker | Install with a package manager |
| Platforms | — | macOS, Windows, Linux, CLI, API |
| Works with | — | VS Code |
| Main language | Go | Go |
| Last code update | 4 days ago | 4 days ago |
What each one is
LocalAI
LocalAI is a self-hosted server that runs many kinds of AI models on your own hardware, including language, vision, voice, image and video models. It exposes an API that is compatible with OpenAI, Anthropic and ElevenLabs, so existing tools can point at it instead of a cloud service. The README says it can run without a GPU and keeps data on your own infrastructure.
Ollama
Ollama is a tool for downloading and running open-weight AI language models locally, with a simple command line and a REST API. The README says it also offers cloud access and can connect to coding tools and assistants such as Claude Code, Codex and OpenClaw. People use it to try models privately or to build apps that call a model through a local API.
Best for
LocalAI
- Developers who want an OpenAI-compatible endpoint running on their own machines or servers
- Teams that need privacy and want data to stay inside their infrastructure
- People experimenting with several model types (text, voice, image) behind one API
- Users with mixed hardware, such as NVIDIA, AMD, Intel, Apple Silicon or CPU-only machines
Ollama
- Developers who want a local model API for their own apps
- People who want to chat with open models without sending prompts to a hosted service
- Users who want to connect a coding assistant to a local or self-chosen model
- Students experimenting with different open models from a terminal
Strengths
LocalAI
- Broad model support across text, vision, voice, image and video, per the README
- Works with several hardware types, including CPU-only setups
- API compatibility with OpenAI, Anthropic and ElevenLabs reduces code changes
Ollama
- Simple install and run commands across macOS, Windows, Linux and Docker
- Official Python and JavaScript libraries plus a documented REST API
- Large community with many integrations listed in the README
Not ideal for
LocalAI
- People who only want a simple desktop chat app; the README focuses on a server and API, though a macOS launcher exists
- Users with very limited disk space, since models and backends are downloaded on demand and can be large
- Those who need a fully managed cloud service with no setup work
Ollama
- People who need the most capable closed frontier models, since this focuses on open models
- Users with limited disk space or memory, because model files can be large and need capable hardware (the README does not give specific requirements)
- Non-technical users who want a polished desktop app with no terminal use, although the README mentions a download option for macOS and Windows
Trade-offs
LocalAI
- Many features and backends make the project complex to configure; the README is long and the docs are external
- Backends are downloaded on demand, so first runs may take time and bandwidth
- The macOS DMG is not signed by Apple, requiring a manual quarantine-removal step
Ollama
- The README is truncated and does not state hardware requirements or model sizes
- Some features, such as cloud access and specific integrations, depend on Ollama's own services and documentation that is only partly described here
- Model quality and licensing depend on each individual model, not on Ollama itself
Getting started
LocalAI
Run CPU-only container
docker run -ti --name local-ai -p 8080:8080 localai/localai:latestRun with NVIDIA GPU (CUDA 12)
docker run -ti --name local-ai -p 8080:8080 --gpus all localai/localai:latest-gpu-nvidia-cuda-12Ollama
macOS and Linux install
curl -fsSL https://ollama.com/install.sh | shWindows install (PowerShell)
irm https://ollama.com/install.ps1 | iexFrequently asked questions
Should I use LocalAI or Ollama?
LocalAI is a self-hosted server that runs many kinds of AI models (text, vision, voice, image, video) behind an OpenAI-compatible API, aimed at developers and teams who want that on their own hardware and are willing to deal with more setup. Ollama is a simpler tool for downloading and running open language models with a few terminal commands, aimed at people who want to chat with open models or build small apps quickly. They overlap on local model serving, but LocalAI is broader and more configurable, while Ollama is easier to start with and centres on language models. Pick LocalAI if you need one self-hosted API that handles text, voice and image models and must match OpenAI, Anthropic or ElevenLabs endpoints in your existing code. Pick Ollama if you want the quickest way to run open language models locally from a terminal and call them from your own apps or a coding assistant.
What is the difference between LocalAI and Ollama?
LocalAI: Open-source engine that runs AI models (text, vision, voice, image, video) locally behind an OpenAI-style API. Ollama: Runs open AI models like Gemma, Qwen and DeepSeek on your own machine or in the cloud. LocalAI suits developers who want an openai-compatible endpoint running on their own machines or servers, while Ollama suits developers who want a local model api for their own apps.
Are LocalAI and Ollama free?
LocalAI: Free and open source. Ollama: Free and open source.
Which is easier to set up, LocalAI or Ollama?
Ollama is easier to get started with (rated beginner); LocalAI is rated intermediate and usually needs more setup.
Is LocalAI or Ollama more popular?
Ollama has more GitHub stars (186k) than LocalAI (50.1k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to LocalAI and Ollama?
Other options people compare them with include llama.cpp, LlamaGPT, Toonflow, GPT-SoVITS, MindsHub.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.