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Ultra-lightweight, self-hosted open-source AI assistant in Go that runs on sub-$10 hardware like Raspberry Pi with under 10MB RAM.
Developer platform serving 200+ optimized LLMs via APIs; high traffic.
Native macOS app that unifies 300+ AI models in one private workspace with agents, MCP tools, and one-time licensing.
Google's agentic development platform and IDE for building software with autonomous, Gemini-powered coding agents.
Weights & Biases is a widely used MLOps platform for experiment tracking, model management and evaluating AI applications.
No public pricing
No public pricing
Free trial available
No public pricing
No public pricing
- ✦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
- ✦Access over 200 optimized models, including LLMs, image, video, and audio processing.
- ✦Achieve low-latency, high-throughput inference with SiliconFlow's self-developed acceleration frameworks.
- ✦Deploy models via serverless inference, dedicated endpoints, or reserved GPUs to suit various workloads.
- ✦Customize models to your data with built-in monitoring and elastic compute resources.
- ✦Ensure data privacy and business security with dynamic scaling and fault tolerance mechanisms.
- ✦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
- ✦Agent-first IDE experience
- ✦Autonomous planning and code execution
- ✦Integrated editor, terminal and browser control
- ✦Powered by Google's Gemini models
- ✦High-level developer supervision
- ✦Experiment tracking and visualization for ML training runs
- ✦Model and artifact versioning and management
- ✦Hyperparameter optimization tooling
- ✦Collaborative dashboards and reports for ML teams
- ✦LLM application tracing and evaluation tooling
- →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
- →Quickly deploy various AI models via a simple API, supporting tasks like text, image, audio, and video processing.
- →Utilize serverless GPUs to automatically scale AI applications, ensuring flexibility and cost-efficiency.
- →Access high-performance GPUs for demanding workloads, such as large-scale inference and video generation.
- →Deploy custom models with guaranteed performance and scalability, tailored to specific business needs.
- →Using multiple AI providers in one place
- →Explaining or fixing on-screen content instantly
- →Building reusable task-specific agents
- →Analyzing documents and screenshots privately
- →Building apps with AI agents
- →Automating multi-step coding tasks
- →Prototyping and iterating on software
- →Assisting developers on complex work
- →ML engineers tracking and comparing training experiments
- →Research teams versioning datasets and model checkpoints
- →Teams building and evaluating LLM-powered applications
- →Organizations collaborating on machine learning projects