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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
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GitFluence
✓ verifiedFree

Free AI helper that turns a plain-English description of a task into the matching Git command to copy and run.

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

5.2K saves
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Opera One Browser
✓ verifiedFree

Free Chromium-based desktop browser with tab grouping, built-in AI, free VPN, ad blocker and sidebar apps.

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Pixels2Flutter
✓ verifiedFree

Turns UI screenshots into working Flutter code.

12K 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

No public pricing

No public pricing

No public pricing

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
  • Natural-language to Git command suggestions
  • AI-driven command matching
  • Copy-ready command output
  • Git guides and reference
  • 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)
  • Tab Islands for organizing tabs into groups
  • Built-in Opera AI assistant with page context
  • Free VPN and ad blocker
  • Modular sidebar with apps and messengers
  • Split-screen browsing and immersive themes
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
  • Find the correct Git command quickly
  • Learn Git syntax by describing a goal
  • Avoid memorizing Git flags
  • Creating and manipulating datasets
  • Training small machine learning models
  • Implementing advanced training and inference logic
  • Building applications that require tensor computations
  • Browsing with organized tab groups
  • Using AI assistance while browsing
  • Protecting privacy with a free VPN
  • Multitasking with sidebar apps and split screen
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