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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.

Windsurf Editor logo
Windsurf Editor
✓ verifiedFree trial

AI-powered code editor with agentic workflows for developers.

3.3M visits/mo
Continue logo
Continue
✓ verifiedFreemium

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

775K visits/mo
Workik logo
Workik
✓ verifiedFreemium

AI coding assistant that gathers project context to plan, generate, test and ship code across the SDLC via IDE and chat integrations.

210K visits/mo
Aider logo
Aider
✓ verifiedFree

Open-source terminal AI pair programmer that edits code in your local git repo and auto-commits, working with most LLMs.

479K visits/mo
Defang logo
Defang
✓ verifiedFreemium

Developer tool that deploys Docker Compose apps (with LLMs and databases) into your own AWS, GCP or Azure account via one command.

20K visits/mo
Pricing

No public pricing

No public pricing

Trial: $0/month (20 AI requests on signup, 7 requests/day, 50 free flow runs, up to 3 users)
Starter: $15/month billed annually or $25/month (20M standard AI tokens, 1,000 flow runs)
Premium: $30/month billed annually or $50/month (40M standard + 4M advanced AI tokens, 3,000 flow runs)
Elite: $80/month billed annually or $150/month (100M standard + 10M advanced AI tokens, 10,000 flow runs)
Tailored: $62/month (custom AI token allocation)

Free trial available

No public pricing

Starter: $0 (1 cloud account)
Pro: $49/mo (1 account, +$29/mo per extra)
Enterprise: $499/mo (3 accounts, +$49/mo per extra)
Core features
  • AI-powered code completion and suggestions
  • Automated lint fixing
  • Cascade agent for advanced coding assistance
  • Integrated app building and deployment
  • MCP server support for custom tools
  • Terminal command integration
  • Memory of codebase structure and workflow
  • Open-source AI code assistant
  • Customizable autocomplete
  • In-editor AI chat
  • Community-built coding agent
  • Automatic context-gathering from connected engineering sources
  • AI-generated code, tests and pull requests from tickets
  • Task planning that breaks complex work into subtasks
  • Auto-updating engineering documentation
  • Vector search over embedded project data
  • Multiple selectable AI models (GPT, Gemini, Claude, Llama, etc.)
  • Engineering productivity analytics dashboard
  • Terminal-based AI pair programming
  • Edits code in your local git repo
  • Automatic git commits with messages
  • Codebase mapping for large projects
  • Works with cloud and local LLMs
  • Voice-to-code, image/web context, lint and test
  • One-command deploy from Docker Compose
  • Deploys into your own or a customer's cloud account
  • Native managed LLM access (Bedrock/Vertex/Azure AI)
  • Managed Postgres, MongoDB and Redis
  • Auto-configured IAM, VPC, TLS and load balancing
  • Open-source CLI and cloud providers
Use cases
  • Accelerating software development by automating repetitive tasks
  • Reducing onboarding time for new developers
  • Improving code quality and reducing tech debt
  • Streamlining the app building and deployment process
  • Enhancing developer productivity by keeping them in a state of flow
  • Get AI code completions while coding
  • Ask questions about code in the editor
  • Build on an open-source coding-agent foundation
  • Engineering teams automating ticket-to-PR workflows
  • Developers wanting AI-assisted debugging and test generation
  • Engineering managers tracking AI-driven productivity gains
  • Teams centralizing documentation from scattered sources
  • Building features and fixing bugs via AI in the terminal
  • Working on large existing codebases
  • Automating git commits
  • Using local LLMs for private coding
  • Shipping AI agents and web apps to production
  • Deploying the same app across many customer clouds
  • Agencies deploying into client cloud accounts
  • Avoiding hand-written Terraform or Kubernetes
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