Control the provider path
Choose provider preferences and fallback models for inference requests.
Hosted gateway
Vercel AI Gateway
Route requests across providers and fallback models with visibility into routing attempts, latency, token usage and cost.
Sources reviewed . Documentation review; not a performance benchmark or runtime test.
What can you do with Vercel AI Gateway?
Inspect routing attempts
Use response metadata and observability to understand the path a request took.
Evaluate application cost
Review token usage, latency and costs alongside output quality.
Before you integrate
Set provider preferences explicitly and inspect response metadata to confirm which provider served the request.
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 Vercel AI Gateway bill.
Check Vercel AI Gateway documentation ↗Sources and corrections
Suggest an update →Compare related routing products
Selected by product type and shared routing capabilities.
OpenRouter →
Access models through one API and control which inference providers serve a request. Provider preferences and fallbacks help manage availability.
Cloudflare AI Gateway →
Manage model requests with logging, caching and rate limits, plus fallback providers for errors or configured timeouts.
Helicone AI Gateway →
Route model requests through an OpenAI-compatible endpoint with provider fallbacks and request observability.