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Project IDX by Google
✓ verifiedFree
Google's cloud-based, AI-assisted development environment, now rebranded and merged into Firebase Studio.
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Aide Dev
✓ verifiedPaid
Aide helps developers code faster with parallel agents and automated workflows.
7.6K visits/mo
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Void Editor
✓ verifiedFree
Free open-source VS Code fork letting developers connect directly to any AI model without a proxy, for privacy-focused coders.
Pricing
No public pricing
No public pricing
Standard: $49 per month
Free Plan: $0 one-time
Hobby: $16/month
Standard: $83/month
Growth: $333/month
Auto Recharge Credits: $11/mo for 1000 credits
Credit Pack: $9/mo for 1000 credits
Enterprise Plan: Contact for Pricing
No public pricing
Core features
- ✦Cloud-based IDE accessible from the browser
- ✦AI-assisted coding
- ✦Cross-platform app development
- ✦Preconfigured workspaces and templates
- ✦Now part of Firebase Studio
- ✦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)
- ✦Parallel Agents for faster coding
- ✦GitHub native integration
- ✦Automated PR workflow
- ✦Smart PR suggestions
- ✦Automatic code reviews
- ✦Real-time progress tracking
- ✦Web scraping
- ✦Web crawling
- ✦Data extraction in Markdown, JSON, and screenshot formats
- ✦Dynamic content handling
- ✦Rotating proxies
- ✦Rate limits management
- ✦Open-source availability
- ✦Media Parsing
- ✦Tab-key autocomplete suggestions
- ✦Inline quick-edit on selected code
- ✦Chat with agent, gather, and normal modes
- ✦Direct connections to any LLM provider, no proxy backend
- ✦One-click import of VS Code themes and settings
- ✦Checkpoints to track and revert LLM-made changes
- ✦Lint error detection
- ✦Fast apply designed for large, 1000+ line files
Use cases
- →Building apps from anywhere in the browser
- →Prototyping with AI assistance
- →Developing cross-platform applications
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Automating code reviews
- →Generating PRs automatically
- →Improving code quality through continuous improvements
- →Powering AI assistants with real-time web content
- →Enhancing sales data with web information
- →Adding scraping capabilities to code editors
- →Enabling customers to build AI apps with web data
- →Extracting comprehensive information for in-depth research
- →Switching from Cursor or Windsurf while keeping data private
- →Running local open models like DeepSeek or Llama instead of paying per API call
- →Connecting directly to frontier models such as Claude or Gemini
- →Editing and refactoring large codebases with AI help
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