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AI Stays Local and LocalAI
An open-source AI engine with drop-in API compatibility for several hosted providers.
When LocalAI is the better fit
- You want an open-source engine that detects your GPU and picks a backend for it today.
- You want distributed or peer-to-peer inference now.
- You want API compatibility with several hosted providers.
Side by side
LocalAI as its own public pages describe it on 2026-09-21, and AI Stays Local at the maturity its product data records. Where a source does not say, the table says so rather than guessing.
| Dimension | LocalAI | AI Stays Local |
|---|---|---|
| Interface | APIs compatible with OpenAI, Anthropic and ElevenLabs, plus a web interface. | Command line and an OpenAI-compatible local API, in private beta for selected testers. A desktop app is planned and not built. |
| Runs models itself | Yes, across several backends. | Yes. Inference sits behind an engine adapter; the recorded profiles run on upstream engines under their own licences. |
| Documents and retrieval | Built-in agents with retrieval and MCP support. | Folders you grant, lexical retrieval, answers that cite file and location, and refusal when the documents do not contain the answer. |
| Hardware planning | Yes. It detects the GPU and downloads a matching backend, and describes automatic fitting of a model across several GPUs. | Evaluates the machine and recommends a model profile (private beta). Each model states execution, validation, usability, hardware and availability separately. |
| More than one machine | Yes. Peer-to-peer inference and a distributed mode are described. | Planned. Multi-node execution is designed and not implemented. |
| Platforms | NVIDIA, AMD, Intel, Apple Silicon, Vulkan and CPU; Docker, a macOS installer and Kubernetes. | Command line on Linux and macOS for selected testers. Measurements published from one Linux ARM64 machine. |
| Licence | MIT. | Commercial product. A Free edition is defined for local use; paid prices are provisional. The runtime is not open source. |
Where AI Stays Local puts its emphasis
- LocalAI detects hardware too. AI Stays Local puts its emphasis on publishing, per model, what was measured, on which machine, and whether it is usable, with the badge derived by fixed rules rather than by speed.
- Its multi-machine design is planned, not implemented, where LocalAI describes distributed inference today.
- Cited document answers with refusal are part of the product.
Sources, checked 2026-09-21: LocalAI repository README. Descriptions of other projects are summaries of their own public pages on that date and may since have changed. No statement here is a claim about another project's security.