Get up and running with Llama 3.3, DeepSeek-R1, Phi-4, Gemma 3, and other large language models.
- MIT
- Go
- Docker
- Actively maintained
AI & LLM Tools comparison
Ollama vs LocalAI: which should you self-host in 2026?
Pick Ollama for the simplest way to download and run local LLMs with one command; pick LocalAI for a drop-in OpenAI API replacement that also serves images, audio and embeddings.
Both are open source and run on your own server. Below: a side-by-side of license, stack and features, live GitHub activity, and our verdict on who should pick which.
Run your AI models locally and generate images and audio (alternative to OpenAI and Claude).
- MIT
- Go
- Docker
- Actively maintained
Head-to-head
Ollama vs LocalAI, side by side
Hand-checked differences first, then live numbers from GitHub, refreshed with every catalog update.
| Aspect |  Ollama |  LocalAI |
|---|---|---|
| License | MIT | MIT |
| Language/stack | Go, built on the llama.cpp/GGML engine | Go API server that orchestrates multiple backends (llama.cpp, diffusers, whisper and others) |
| Scope | Text and vision LLMs plus embeddings | LLMs, embeddings, image generation, text to speech and speech to text |
| API | Native REST API plus OpenAI-compatible endpoints | Designed as an OpenAI API drop-in replacement first |
| Model management | Curated library: ollama pull fetches ready-to-run models; Modelfiles customise them | Model gallery plus YAML configs to load models from Hugging Face or files |
| Installation | Native installers for macOS, Windows and Linux, plus a Docker image | Docker images (CPU and GPU variants) and a single binary |
| GitHub stars | 182,289 | 49,405 |
| Commits, last 12 months | 1,083 | 3,438 |
| Last commit | Oct 6, 2026 | Oct 6, 2026 |
| Latest release | v0.35.1Sep 29, 2026 | v4.11.0Oct 2, 2026 |
| Main language | Go | Go |
| Official Docker image | Yes | Yes |
| Repository | ollama/ollama | mudler/LocalAI |
Swipe the table sideways to see both apps. GitHub figures come from the public API. Highlighted values are the higher of the two.
Verdict
Ollama is the easiest way to run open models locally: one install, the ollama run command, and a curated model library that handles quantised downloads for you. LocalAI is the better fit when you need a self-hosted stand-in for the full OpenAI API surface, including image generation, speech and transcription, across several inference backends.
Best for
Choose Ollama for
Developers who want to run open LLMs locally with minimal setup.
Best for
Choose LocalAI for
Teams replacing the OpenAI API with one self-hosted multi-modal endpoint.
Deploy either in minutes
Not sure yet? Spin up a small VPS or a managed instance, try both for a week, and keep the one that fits.
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Can Ollama and LocalAI run without a GPU?
Yes. Both run quantised models on the CPU, though a supported GPU makes generation much faster.
Do both work with OpenAI client libraries?
Yes. Ollama exposes OpenAI-compatible endpoints alongside its own API, and LocalAI is built to mimic the OpenAI API so most clients only need a new base URL.
Which should I pair with a chat UI like Open WebUI?
Ollama is the most common pairing and is supported natively by Open WebUI. LocalAI also works through its OpenAI-compatible API.
Which is more popular on GitHub, Ollama or LocalAI?
Ollama has 182,289 GitHub stars against 49,405 for LocalAI. Over the last twelve months Ollama received 1,083 commits and LocalAI received 3,438, so LocalAI is the more actively developed of the two right now. Stars measure interest, not fit, so weigh them against the differences above.
