Compare tools
Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.
⇄ Comparison dimension — pick the market you're actually shopping in
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
Agentic AI platform with a coding desktop app, CLI, and cloud agents for autonomous software development and office work.
Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
Free Chromium-based desktop browser with tab grouping, built-in AI, free VPN, ad blocker and sidebar apps.
No public pricing
No public pricing
No public pricing
Free trial available
No public pricing
Free trial available
No public pricing
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
- ✦Multi-agent collaboration for end-to-end tasks
- ✦Persistent memory and custom rules
- ✦Extensible skills and plugins
- ✦Rich context across code, images, and directories
- ✦Automatic codebase documentation generation
- ✦Terminal-native CLI and JetBrains IDE plugin
- ✦Cloud-hosted agents for enterprise use
- ✦Publish structured documentation sites
- ✦Git sync for docs-as-code workflows
- ✦AI setup agent to build and import docs
- ✦GitBook MCP server for AI access
- ✦Enterprise controls
- ✦Free tier to start
- ✦Tab Islands for organizing tabs into groups
- ✦Built-in Opera AI assistant with page context
- ✦Free VPN and ad blocker
- ✦Modular sidebar with apps and messengers
- ✦Split-screen browsing and immersive themes
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Autonomous feature development in large codebases
- →Terminal-based AI pair programming
- →Cross-department task automation for legal, finance, HR
- →Onboarding developers to unfamiliar codebases
- →Publish product and API documentation
- →Maintain docs-as-code with Git sync
- →Make docs consumable by AI assistants
- →Import existing docs into a hosted site
- →Browsing with organized tab groups
- →Using AI assistance while browsing
- →Protecting privacy with a free VPN
- →Multitasking with sidebar apps and split screen