PortkeyvsVercel AI Gateway

Full side-by-side comparison — features, pricing, platforms, and which one wins in 2026.

Portkey

LLM APIs & Inference

AI gateway for reliable and fast LLM applications

Full review →Website ↗

Vercel AI Gateway

LLM APIs & Inference

Unified API gateway for routing app calls across hundreds of AI models

Full review →Website ↗
FeaturePortkeyVercel AI Gateway
CategoryLLM APIs & InferenceLLM APIs & Inference
PricingFree + Pro plansFree monthly credits; pay-as-you-go at provider list price with no markup
GitHub Stars
✓ More stars
6k
—
PlatformsWeb, DockerWeb, API
Key Features
  • ✓ AI gateway
  • ✓ Fallbacks
  • ✓ Load balancing
  • ✓ Caching
  • ✓ Observability
  • ✓ Single API key
  • ✓ Hundreds of models
  • ✓ Unified model API
  • ✓ Provider routing and fallbacks
  • ✓ Automatic retries
  • ✓ Usage and spend monitoring
  • ✓ Bring Your Own Key
  • ✓ AI SDK and OpenAI-compatible APIs
Pros
  • + Automatic fallbacks
  • + Load balancing
  • + Request caching
  • + Observability built-in
  • + Open-source gateway
  • + One endpoint for many model providers
  • + Centralized usage, spend, and observability
  • + Automatic retries and fallbacks improve production resilience
  • + No token markup according to Vercel docs
  • + Works with AI SDK and OpenAI-compatible API clients
Cons
  • − Added infrastructure layer
  • − Learning curve
  • − Some features need Pro
  • − Latency overhead
  • − Best fit for teams already building web apps or using Vercel/AI SDK
  • − Underlying provider terms and model limits still apply
  • − BYOK fallback can still consume AI Gateway credits
  • − Exact model pricing should be checked in the current Gateway model list
Tags
gatewayreliabilityobservabilityapi
ai-gatewaymodel-routingvercelai-sdkllm-apibyokobservability

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