Apigee AI Gateway vs Helicone (2026)
Updated March 10, 2026
Overview
Google Cloud's Apigee includes AI gateway capabilities for managing and securing generative AI API traffic, with model routing, token-based rate limiting, content moderation, and comprehensive analytics.
Helicone is an open-source LLM observability and proxy platform. By adding a single line of code, developers get request logging, cost tracking, caching, rate limiting, and analytics for their LLM applications. Helicone supports all major LLM providers and can function as both a gateway proxy and a logging-only integration.
Key features
Core capabilities each platform advertises.
- Google Cloud AI traffic management
- API analytics and monitoring
- Security and threat protection
- Rate limiting and quotas
- Multi-cloud support
- LLM observability and monitoring
- Cost tracking and analytics
- Request caching
- Rate limiting and user management
- Open-source with managed option
Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- Production-ready
- Good performance
- Active development
Cons
- Pricing varies
- Setup required
Pros
- Extremely simple integration (one line of code)
- Open-source with self-hosting option
- Generous free tier (100k requests)
- Supports all major LLM providers
Cons
- Advanced features require paid tiers
- Data retention limited on free tier
- Self-hosting requires technical expertise
Apigee AI or Helicone — which should you choose?
Choose Apigee AI if you wantChoose if you want
- Managing AI APIs on Google Cloud
- Enterprise API security for AI endpoints
- Usage metering and billing for AI services
- Multi-cloud AI API management
- Compliance and governance for AI traffic
Choose Helicone if you wantChoose if you want
- LLM cost monitoring and optimization
- Production request debugging
- User-level usage tracking and rate limiting
- Caching to reduce latency and cost
- Team-wide LLM spend management
Compare Apigee AI Gateway and Helicone on your own traffic
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