Compare tools
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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Apify
✓ verifiedFreemium
Full-stack platform for web scraping, data extraction, and automation; category leader.
👁 4.4M/mo♥ 2.0K
✕
Claude
✓ verifiedFreemium
Anthropic's official domain and Claude model line; category-defining AI lab.
👁 22M/mo♥ 231K
Pricing
Free: $0/mo ($5 included usage)
Starter: $29/mo ($26/mo billed annually)
Scale: $199/mo ($179/mo billed annually)
Business: $999/mo ($899/mo billed annually)
Free trial available
No public pricing
Free: $0
Pro: $17/mo annual ($20 monthly)
Max: from $100/mo (5x or 20x usage)
Team Standard: $20/seat/mo annual ($25 monthly)
Team Premium: $100/seat/mo annual ($125 monthly)
Enterprise: $20/seat + API usage
Free trial available
No public pricing
Core features
- ✦Web scraping
- ✦Data extraction
- ✦Browser automation
- ✦AI agents
- ✦Anti-blocking
- ✦Proxy rotation
- ✦Open-source tools (Crawlee)
- ✦Ready-made tools and code templates
- ✦AI-powered code autocompletion
- ✦Context-aware code referencing and chat
- ✦Natural language code editing
- ✦Customizable AI code assistants
- ✦Advanced reasoning
- ✦Vision analysis
- ✦Code generation
- ✦Multilingual processing
- ✦API access
- ✦Collaboration tools
- ✦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)
Use cases
- →Data for generative AI
- →Lead generation
- →Market research
- →Sentiment analysis
- →Accelerate development with AI-powered autocompletion.
- →Improve code understanding with context-aware chat.
- →Refactor code using natural language instructions.
- →Collaborating on complex cognitive tasks
- →Transcribing and analyzing images
- →Generating code for websites and applications
- →Translating between languages
- →Building AI agents
- →Providing customer support
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
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