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Open-source desktop app for running AI chat models locally or via APIs, as a private ChatGPT alternative.
Native macOS app that unifies 300+ AI models in one private workspace with agents, MCP tools, and one-time licensing.
Ultra-lightweight, self-hosted open-source AI assistant in Go that runs on sub-$10 hardware like Raspberry Pi with under 10MB RAM.
Unified API and gateway routing requests across 200+ models from 40+ providers, with cost tracking and a free BYOK tier.
Free crowdsourced benchmark that pits top AI models head-to-head on design tasks and ranks them by public votes.
No public pricing
Free trial available
No public pricing
Free trial available
No public pricing
- ✦Run open-source LLMs locally
- ✦Connect to online models (OpenAI, Claude, Gemini)
- ✦Private, offline-capable AI chat
- ✦Open source and self-hostable
- ✦Model library via Hugging Face
- ✦Cross-platform desktop app
- ✦Switch across 300+ hosted and local AI models
- ✦Native macOS app with global shortcut and screenshot-to-answer
- ✦Reusable agents, projects, and forked chats
- ✦Multimodal analysis of PDFs, images, and code
- ✦MCP tools and code execution
- ✦Local chat storage with encryptable API keys
- ✦Single self-contained binary requiring under 10MB RAM
- ✦Sub-1-second startup even on low-power processors
- ✦Support for 16+ chat channels including Telegram, Discord, Slack, WeCom
- ✦Compatibility with multiple LLM providers (OpenAI, Claude, DeepSeek, Gemini, etc.)
- ✦Runs on Raspberry Pi, RISC-V, ARM64, x86_64, Android, and Docker
- ✦Self-hosted design keeping data and configuration local
- ✦Gateway/API mode for connecting to chat platforms via MCP protocol
- ✦One API for 200+ models across 40+ providers
- ✦Provider switching without code changes
- ✦Real-time cost tracking
- ✦Bring-your-own-keys, free forever
- ✦Observability and guardrails
- ✦SOC 2 Type II certified
- ✦Side-by-side model output comparison
- ✦Public voting on results
- ✦Leaderboards ranking AI models by 'taste'
- ✦Coverage of websites, games, 3D, UI, images, logos, SVG, video and slides
- →Private local AI chat
- →Using multiple models in one app
- →Avoiding cloud data sharing
- →Experimenting with open models
- →Using multiple AI providers in one place
- →Explaining or fixing on-screen content instantly
- →Building reusable task-specific agents
- →Analyzing documents and screenshots privately
- →Running a private AI assistant on minimal or embedded hardware
- →Local code assistance that keeps proprietary code off the cloud
- →Home automation and personal task scheduling via chat bots
- →Privacy-conscious users wanting self-hosted AI on low-cost devices
- →Route across many LLM providers from one API
- →Track and control AI spend
- →Avoid vendor lock-in with provider switching
- →Compare which AI model produces the best design output
- →Track AI design model rankings
- →Discover models for a specific creative task