LiteLLMvsPhidata

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

LiteLLM

LLM APIs & Inference

Unified API proxy for 100+ LLM providers — one interface, any model

Phidata

AI Agent Frameworks

Build AI agents with memory, knowledge, and tools

FeatureLiteLLMPhidata
CategoryLLM APIs & InferenceAI Agent Frameworks
PricingFree (open-source), hosted proxy availableFree (open-source) + Cloud
GitHub Stars
More stars
16k
15k
PlatformsLinux, macOS, DockerLinux, macOS, Windows
Key Features
  • Unified API for 100+ LLM providers
  • Load balancing across multiple API keys/providers
  • Automatic fallbacks when providers fail
  • Spend tracking and budget alerts per team/project
  • Rate limiting and retry logic built-in
  • OpenAI SDK compatible — zero code changes
  • Self-hostable proxy server
  • Supports streaming, function calling, vision
  • Agent memory
  • Knowledge base
  • Tool use
  • Structured output
  • Multi-model
Pros
  • + One API for 100+ providers
  • + Built-in load balancing and fallbacks
  • + Spend tracking and rate limiting
  • + OpenAI SDK compatible
  • + Clean, Pythonic API
  • + Built-in memory and knowledge
  • + Production-focused
  • + Good documentation
  • + Multi-model support
Cons
  • Adds a proxy layer (slight latency)
  • Complex config for advanced features
  • Rebranding confusion (Phidata→Agno)
  • Smaller community than LangChain
  • Some features require cloud
  • Less flexible for custom setups
Tags
api-gatewaymulti-providerproxyopen-source
agentsmemoryknowledgepython

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