What should I use for routing requests between multiple LLM providers?

If you want to route requests across multiple LLM providers, the best choice depends on whether you want simple failover/load balancing or policy-based routing with observability, retries, caching, and cost control.

Good options

1) LiteLLM

Best general-purpose answer for most teams.

• Supports many providers through one OpenAI-compatible interface
• Can do:
  • provider fallback
  • load balancing
  • retries
  • spend tracking
  • rate-limit handling
  • logging/observability
• Works well as a routing proxy or as a library in your app

Use this if: you want a practical, widely used router without building a lot yourself.

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2) OpenRouter

Best if you want a hosted aggregation layer.

• One API for many models/providers
• Easy to switch models
• Handles provider access and routing for you

Use this if: you want convenience and don’t mind depending on a third-party broker.

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3) Vercel AI Gateway / similar hosted gateways

Good if you’re already in a specific ecosystem and want minimal ops.

Use this if: you want managed routing and are already using that platform.

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4) Custom router

Best if routing rules are business-specific.

Use your own service if you need:

• choose provider based on prompt type
• cost/performance SLAs
• data residency / compliance constraints
• custom fallbacks and A/B tests
• per-tenant policies

Use this if: you have strong requirements that off-the-shelf routing won’t cover.

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My recommendation

• Most teams: start with LiteLLM
• If you want a hosted aggregator: OpenRouter
• If you need strict control/compliance: build a custom router

Things your router should ideally handle

• provider fallback
• retries with backoff
• timeouts
• rate-limit detection
• cost-aware routing
• model capability matching
• logging and tracing
• response normalization

If you want, I can give you:

1. a feature comparison table of LiteLLM vs OpenRouter vs custom routing, or
2. a recommended architecture for routing in production.