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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.

Replicate AI logo
Replicate AI
✓ verifiedPaid

Pay-per-use cloud API to run, fine-tune, and deploy thousands of open-source and proprietary AI models with one line of code.

1.3M visits/mo17K saves
Claude logo
Claude
✓ verifiedFreemium

Anthropic's AI assistant for writing, coding, and analysis across web, mobile, and desktop, plus a developer API.

22M visits/mo231K saves
4.4M visits/mo
Pricing
CPU (Small): $0.000025/sec ($0.09/hr)
Nvidia A100 80GB: $0.0014/sec ($5.04/hr)
Nvidia H100: $0.001525/sec ($5.49/hr)

Free trial available

Free: $0
Pro: $17/month billed annually ($200 up front), or $20/month
Max: From $100/month
Team: $20/seat/month billed annually ($25 monthly); premium seats $100/seat/month annually ($125 monthly)
Enterprise: Contact sales

No public pricing

Core features
  • One-line API calls to run community and proprietary AI models
  • Support for image, video, speech, and LLM generation models
  • Fine-tuning and custom model deployment via Cog
  • Per-second usage billing on shared or dedicated hardware
  • Automatic scaling for high-traffic private models
  • Thousands of community-published models with production APIs
  • Conversational writing and editing
  • Code generation and debugging (Claude Code)
  • Data analysis and visualization
  • Web search plus memory across chats
  • Connectors and remote MCP integrations
  • Extended thinking for complex tasks
  • Dialogue with GLM large model
  • AI search
  • AI drawing
  • AI reading
  • AI-generated video (沉思清影-AI生视频)
  • AI-generated PPT
  • Data analysis tools
  • Code assistance (代码速写)
  • Intelligent agents
Use cases
  • Developers embedding image/video/speech generation into an app via API
  • Teams deploying and scaling their own fine-tuned models
  • Builders comparing outputs from multiple AI models in one playground
  • Companies avoiding GPU infrastructure management for ML inference
  • Drafting and refining written content
  • Building and debugging software
  • Analyzing datasets for insights
  • Research and learning support
  • Team and enterprise automation
  • Engaging in conversations with an AI model
  • Generating images and videos using AI
  • Creating presentations with AI assistance
  • Analyzing data with AI tools
  • Assisting with code development
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