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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.

OpenRouter logo
OpenRouter
✓ verifiedFreemium

Unified API gateway that routes requests to 400+ LLMs across 70+ providers with failover and no subscription.

17M visits/mo
Google Antigravity logo
Google Antigravity
✓ verifiedFree

Google's agentic development platform and IDE for building software with autonomous, Gemini-powered coding agents.

22M visits/mo18K saves
27K visits/mo
liteLLM logo
liteLLM
✓ verifiedFreemium

Open-source AI gateway giving dev teams unified access, fallbacks and spend tracking across 100+ LLMs.

703K visits/mo
Pricing
Free: $0 (free models only, 50 requests/day)
Pay-as-you-go: 5.5% platform fee on inference

No public pricing

No public pricing

Open Source: $0 (self-hosted, 100+ providers)

Free trial available

Core features
  • One unified, OpenAI-compatible API for 400+ models
  • Automatic provider failover for higher uptime
  • Edge routing for low latency
  • Custom data and provider policies
  • Pay-as-you-go credits usable across any model
  • Agent-first IDE experience
  • Autonomous planning and code execution
  • Integrated editor, terminal and browser control
  • Powered by Google's Gemini models
  • High-level developer supervision
  • Open-Source AI Gateway
  • Multi-LLM Management & Cost Optimization
  • Efficient and Secure LLMs Invocation
  • Unified API Signature for LLMs
  • Load Balancer for seamless switching between LLMs
  • Fine-Grained Traffic Control for LLMs
  • LLM Quota Management
  • Real-time LLM Traffic Monitoring
  • Caching Strategies for AI in Production
  • Flexible Prompt Management
  • Unified access to 100+ LLMs in OpenAI format
  • Cost/spend tracking per key, user and team
  • Budgets and rate limiting
  • Automatic provider fallbacks and retries
  • Virtual keys and team management
  • Logging and observability integrations
Use cases
  • Accessing many LLMs through one integration
  • Adding provider redundancy to AI apps
  • Comparing model price and performance
  • Powering agents and AI-native products
  • Building apps with AI agents
  • Automating multi-step coding tasks
  • Prototyping and iterating on software
  • Assisting developers on complex work
  • Building API portals for secure sharing of internal APIs with partners.
  • Tracking API usage and driving API monetization.
  • Managing and securing API access in compliance with enterprise policies.
  • Connecting to multiple AI large models simultaneously.
  • Optimizing LLM costs and improving efficiency.
  • Protecting against LLM attacks and data leaks.
  • Giving developers governed access to many LLMs
  • Attributing and controlling LLM spend
  • Keeping apps running during provider outages
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