Define fallback behavior
Configure alternative providers for failed requests or timeouts.
Hosted gateway
Cloudflare AI Gateway
Manage model requests with logging, caching and rate limits, plus fallback providers for errors or configured timeouts.
Sources reviewed . Documentation review; not a performance benchmark or runtime test.
What can you do with Cloudflare AI Gateway?
Control request traffic
Review caching and rate limits as part of gateway setup.
Inspect failures
Use request logging to investigate errors before changing routing policy.
Before you integrate
Define error and timeout behavior, and verify the authentication requirements of the endpoint you use.
Test against your own workload
Compare successful responses, latency and the total bill, including retries and fallbacks. Verify streaming, tool calls and structured output on the routes you plan to use. These are evaluation steps, not claims that every feature is supported.
Check model-provider incidents →Pricing and model access
Model rates, platform fees, credits and eligibility can change. Check the publisher’s current terms before choosing a route. Our calculator estimates model token costs; it does not quote a negotiated Cloudflare AI Gateway bill.
Check Cloudflare AI Gateway documentation ↗Sources and corrections
Suggest an update →Compare related routing products
Selected by product type and shared routing capabilities.
Vercel AI Gateway →
Route requests across providers and fallback models with visibility into routing attempts, latency, token usage and cost.
Helicone AI Gateway →
Route model requests through an OpenAI-compatible endpoint with provider fallbacks and request observability.
Requesty →
Send model requests through an OpenAI-compatible endpoint with fallback, load-balancing and latency-based routing policies.