Vercel AI GatewayvsSemantic Kernel

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

Vercel AI Gateway

LLM APIs & Inference

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

Full review →Website ↗

Semantic Kernel

Developer Tools

Microsoft's AI orchestration SDK for building agents with .NET, Python, and Java

Full review →Website ↗
FeatureVercel AI GatewaySemantic Kernel
CategoryLLM APIs & InferenceDeveloper Tools
PricingFree monthly credits; pay-as-you-go at provider list price with no markupFree (open-source)
GitHub Stars—
✓ More stars
23k
PlatformsWeb, APILinux, macOS, Windows
Key Features
  • ✓ 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
  • ✓ Plugin system
  • ✓ Memory
  • ✓ Planner
  • ✓ Multi-language
  • ✓ Azure integration
Pros
  • + 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
  • + Enterprise-ready with Microsoft backing
  • + Multi-language (C#, Python, Java)
  • + Deep Azure OpenAI integration
  • + Plugin architecture for extensibility
Cons
  • − 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
  • − Heavy enterprise focus
  • − Verbose API compared to alternatives
Tags
ai-gatewaymodel-routingvercelai-sdkllm-apibyokobservability
microsoftsdkenterprisedotnet

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