Local-first MacOS AI application - 100% Private, Works Fully Offline.
LocalChat is a Mac application that runs large language models entirely on-device, without sending data to a cloud server. It reads full documents directly — including PDF, Markdown, CSV, XLSX, PNG, and TXT files — rather than requiring text to be pasted in, and organizes work into per-project workspaces that can be restricted to answer only from files within that project. It also supports connecting to an Obsidian vault, indexing notes and links as searchable memory.
The application ships with a curated library of over 300 open-source models optimized for Apple Silicon, spanning reasoning, vision, OCR, image generation, and embedding models, and supports loading any GGUF model from Hugging Face by URL or file. Models can be swapped mid-conversation. No account or login is required, and no internet connection is needed once the app is installed and a model is downloaded.
It targets professionals handling sensitive or regulated material — lawyers, therapists, doctors, accountants, consultants, and researchers — where cloud-based AI tools may conflict with confidentiality, privilege, or compliance obligations. Pricing is a one-time license rather than a subscription: a Single license (one Mac) is listed at $49.50 (discounted from $99), a Family license (up to 5 devices) at $199.50 (discounted from $399), both including one year of updates, and a custom-priced Team license for organizations needing volume licensing and deployment support. Purchases include a 30-day money-back guarantee.
A Single license for one Mac is $49.50 (50% launch discount off $99) with 1 year of updates; a Family license for up to 5 devices is $199.50, and Team licensing is custom.
No, LocalChat is a one-time purchase rather than a subscription.
LocalChat is a Mac-native app, tested on Apple Silicon.
No, LocalChat processes 100% on-device and works fully offline once installed.
It supports a curated catalog of 25+ on-device models (reasoning, vision, OCR, image generation, embeddings) plus any GGUF model from Hugging Face.
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