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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.

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
devActivity logo
devActivity
✓ verifiedFreemium

GitHub-based engineering analytics that tracks contributions, automates performance reviews and adds gamification for dev teams.

52K visits/mo

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

5.2K saves
Apify logo
Apify
✓ verifiedFreemium

Full-stack platform for web scraping, data extraction, and automation; category leader.

4.4M visits/mo2.0K saves
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Debugg AI
✓ verifiedFreemium

Zero-config AI browser testing that auto-runs end-to-end tests on every GitHub PR and posts results as comments.

3.0K visits/mo6.3K saves
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/contributor (up to 7 contributors, 90-day retention)
Premium: $10/contributor (unlimited contributors, AI insights)

No public 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

Free: $0 (public repos, 100 tests/mo)
Pro: $20/mo (private repos, 1,000 tests/mo)
Grow: $40/mo (5,000 tests/mo)
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
  • Contribution and work-quality analytics
  • Automated, AI-powered performance reviews
  • Retrospective insights
  • Operational bottleneck alerts
  • Gamification with XP, levels and leaderboards
  • Uses Git metadata without accessing source code
  • 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)
  • Web scraping
  • Data extraction
  • Browser automation
  • AI agents
  • Anti-blocking
  • Proxy rotation
  • Open-source tools (Crawlee)
  • Ready-made tools and code templates
  • No-config automated browser testing
  • GitHub-native PR testing with inline results
  • Fully managed cloning, build, and tunneling
  • AI app mapping and targeted test generation
  • Recorded, replayable test sessions
  • MCP server for Claude and Codex
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
  • Automating developer performance reviews
  • Spotting delivery bottlenecks
  • Generating retrospective insights
  • Motivating teams via gamification
  • Creating and manipulating datasets
  • Training small machine learning models
  • Implementing advanced training and inference logic
  • Building applications that require tensor computations
  • Data for generative AI
  • Lead generation
  • Market research
  • Sentiment analysis
  • Catch UI regressions before merge
  • Test user flows automatically on each PR
  • Validate flows against a local dev server
  • Replace hand-written Playwright/Selenium suites
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