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Google's agentic development platform and IDE for building software with autonomous, Gemini-powered coding agents.
Anthropic's AI assistant for writing, coding, and analysis across web, mobile, and desktop, plus a developer API.
AI research lab building multimodal 'omni' foundation models and infrastructure aimed at robotics and physical-world applications.
Native macOS app that unifies 300+ AI models in one private workspace with agents, MCP tools, and one-time licensing.
Open-source library and desktop app for fast, memory-efficient local fine-tuning and inference of open LLMs.
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No public pricing
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No public pricing
- ✦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
- ✦Conversational writing and editing
- ✦Code generation and debugging (Claude Code)
- ✦Data analysis and visualization
- ✦Web search plus memory across chats
- ✦Connectors and remote MCP integrations
- ✦Extended thinking for complex tasks
- ✦Omni multimodal model research and development
- ✦Real-time inference API (Infer) for enterprise use
- ✦Video tagging, search, and clipping infrastructure
- ✦Training data generation from egocentric and robotics footage
- ✦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
- ✦Optimized LoRA/FFT/PT training kernels for 500+ models
- ✦Local offline model runner for Mac and Windows
- ✦No-code dataset creation from PDFs, CSVs, and JSON
- ✦Unlimited tool-calling and web search inside model runs
- ✦Data Recipes workflow to turn documents into training datasets
- ✦Export to safetensors or GGUF for llama.cpp, vLLM, Ollama
- ✦Multi-GPU support on paid tiers
- →Building apps with AI agents
- →Automating multi-step coding tasks
- →Prototyping and iterating on software
- →Assisting developers on complex work
- →Drafting and refining written content
- →Building and debugging software
- →Analyzing datasets for insights
- →Research and learning support
- →Team and enterprise automation
- →Powering robotics perception with multimodal AI
- →Running large-scale video search and analysis via API
- →Sourcing specialized training data for frontier AI 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
- →ML engineers fine-tuning open models on a single GPU for free
- →Teams building custom datasets from unstructured documents
- →Developers wanting to run and compare LLMs fully offline
- →Enterprises needing faster, more accurate multi-node training