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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

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✓ verifiedFreemium

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

👁 775K/mo

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

5.2K
Gitmore
✓ verifiedFreemium

Turns Git commits and PRs into AI-summarized daily or weekly reports delivered to Slack or email, no source access.

👁 7.6K/mo
👁 1.5M/mo
Code Autopilot
✓ verifiedFreemium

AI GitHub companion that summarizes PRs, answers questions and proposes fixes inside issues and pull requests.

Pricing

No public pricing

No public pricing

No public pricing

Free trial available

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
  • 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)
  • AI-summarized commit and PR reports
  • Daily and weekly scheduled digests
  • Slack and email delivery
  • One-click OAuth or webhook setup
  • GitHub, GitLab and Bitbucket support
  • Templates for standups and reports
  • 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
  • Chat inside GitHub issues and PRs
  • Task-to-implementation plans with code
  • Automatic bug-fix suggestions
  • Pull-request summaries for faster review
  • Full-codebase context
  • GitHub-native integration
Use cases
  • 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
  • Keep stakeholders updated on what shipped
  • Replace manual status updates and standups
  • Give teams visibility into Git activity
  • 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
  • Speeding up pull-request reviews
  • Implementing features from task descriptions
  • Debugging with AI-proposed solutions
  • Answering questions about a repo
  • Boosting a solo developer's output
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