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✓ verifiedFreemium

Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.

👁 775K/mo
GitFluence
✓ verifiedFree

Free AI helper that turns a plain-English description of a task into the matching Git command to copy and run.

Thin 'Lingbot-map' agent listing on github.com with zero traffic; too thin to tell.

5.2K
Gemini Code Assist
✓ verifiedFreemium

Google's AI coding assistant for code completion, generation, chat and review across IDEs and GitHub.

👁 559K/mo
Artificial Analysis
✓ verifiedFreemium

Independent benchmarks comparing AI models and API providers on intelligence, speed, and cost across many leaderboards.

Pricing

No public pricing

No public pricing

No public pricing

No public pricing

No public pricing

Core features
  • Open-source AI code assistant
  • Customizable autocomplete
  • In-editor AI chat
  • Community-built coding agent
  • Natural-language to Git command suggestions
  • AI-driven command matching
  • Copy-ready command output
  • Git guides and reference
  • 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)
  • AI code completion and suggestions
  • Natural-language code generation
  • In-IDE chat assistance
  • AI code review
  • IDE integrations (VS Code, JetBrains, etc.)
  • GitHub integration
  • Intelligence Index across many benchmarks
  • Model speed and cost comparisons
  • Coding, speech, image, and video leaderboards
  • Provider performance analysis
  • Personalized model recommender
  • Premium data and reports
Use cases
  • Get AI code completions while coding
  • Ask questions about code in the editor
  • Build on an open-source coding-agent foundation
  • Find the correct Git command quickly
  • Learn Git syntax by describing a goal
  • Avoid memorizing Git flags
  • Creating and manipulating datasets
  • Training small machine learning models
  • Implementing advanced training and inference logic
  • Building applications that require tensor computations
  • Speeding up coding with AI completions
  • Generating code from plain-language prompts
  • Getting in-editor help and explanations
  • Reviewing pull requests with AI
  • Understanding unfamiliar codebases
  • Choosing an AI model or provider
  • Tracking frontier model progress
  • Comparing price and performance
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