PortkeyvsPhidata

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 ↗

Phidata

AI Agent Frameworks

Build AI agents with memory, knowledge, and tools

Full review →Website ↗
FeaturePortkeyPhidata
CategoryLLM APIs & InferenceAI Agent Frameworks
PricingFree + Pro plansFree (open-source) + Cloud
GitHub Stars
6k
✓ More stars
15k
PlatformsWeb, DockerLinux, macOS, Windows
Key Features
  • ✓ AI gateway
  • ✓ Fallbacks
  • ✓ Load balancing
  • ✓ Caching
  • ✓ Observability
  • ✓ Agent memory
  • ✓ Knowledge base
  • ✓ Tool use
  • ✓ Structured output
  • ✓ Multi-model
Pros
  • + Automatic fallbacks
  • + Load balancing
  • + Request caching
  • + Observability built-in
  • + Open-source gateway
  • + Clean, Pythonic API
  • + Built-in memory and knowledge
  • + Production-focused
  • + Good documentation
  • + Multi-model support
Cons
  • − Added infrastructure layer
  • − Learning curve
  • − Some features need Pro
  • − Latency overhead
  • − Rebranding confusion (Phidata→Agno)
  • − Smaller community than LangChain
  • − Some features require cloud
  • − Less flexible for custom setups
Tags
gatewayreliabilityobservabilityapi
agentsmemoryknowledgepython

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