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local.ai
Experiment with AI models locally without the need to setup a full-blown ML stack. Powered by a native app designed to simplify the whole process from model downloading to starting an inference server. No GPU required!
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Main Features & Characteristics
- Powerful Native App: Built with a Rust backend, local.ai is memory efficient and compact (<10MB on Mac M2, Windows, and Linux .deb).
- CPU Inferencing: Supports CPU inferencing, adapts to available threads, and supports GGML quantization (q4, 5.1, 8, f16).
- Model Management: Keep track of AI models in one centralized location, directory agnostic; features a resumable, concurrent downloader and usage-based sorting.
- Digest Verification: Ensure model integrity with robust BLAKE3 and SHA256 digest compute features; includes a known-good model API, license and usage chips, BLAKE3 quick check, and model info card.
- Inferencing Server: Start a local streaming server for AI inferencing in 2 clicks (Load model, then start server); includes a quick inference UI, writes to .mdx, inference params, and remote vocabulary.
Workflow
Start an inference session (e.g., with WizardLM 7B model) in 2 clicks. Powers any AI app, offline or online (e.g., in tandem with window.ai).
Supported Platforms
Available for Windows (.MSI, .EXE), macOS (M1/M2, Intel), and Linux (AppImage, .deb).
Pricing
Free and open-source, source codes are licensed under GPLv3.
Upcoming Features
GPU Inferencing, Parallel session, Nested directory, Custom Sorting and Searching, Model Explorer, Model Search, Model Recommendation, Server Manager, /audio, /image.
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