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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
Angular.dev
✓ verifiedFree

Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.

👁 1.1M/mo
Cody
✓ verifiedPaid

Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.

👁 245K/mo
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/mo
Pricing

No public pricing

No public pricing

Enterprise: starting at $16K (includes AI feature credits, scales with team size)
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
  • Open-source AI code assistant
  • Customizable autocomplete
  • In-editor AI chat
  • Community-built coding agent
  • Signals-based fine-grained reactivity
  • Built-in control flow and deferrable views
  • Server-side rendering and hydration
  • First-party routing, forms and dependency injection
  • AI-forward tooling and MCP resources
  • In-browser tutorials and playground
  • Codebase-aware developer chat
  • AI code completions and inline edits
  • Customizable and shareable prompts
  • Automatic bug identification and debugging help
  • Context filters to exclude sensitive repos
  • Integrates with major code hosts and IDEs
  • 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
  • Get AI code completions while coding
  • Ask questions about code in the editor
  • Build on an open-source coding-agent foundation
  • Building scalable single-page apps
  • Enterprise web application development
  • Performance-critical front ends
  • Learning modern web development
  • Engineers asking questions about an unfamiliar large codebase
  • Teams standardizing common coding tasks with shared prompts
  • Developers debugging errors faster with AI-assisted context
  • Enterprises running large-scale code migrations
  • 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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