LangChainvsLiteLLM

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

LangChain

AI Agent Frameworks

Framework for building applications with large language models

LiteLLM

LLM APIs & Inference

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

FeatureLangChainLiteLLM
CategoryAI Agent FrameworksLLM APIs & Inference
PricingFree + LangSmith paidFree (open-source), hosted proxy available
GitHub Stars
More stars
98k
16k
PlatformsmacOS, Linux, WindowsLinux, macOS, Docker
Key Features
  • Chain composition
  • RAG pipelines
  • Agent toolkits
  • Memory systems
  • Streaming
  • Multi-model
  • LangGraph
  • 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
Pros
  • + Massive ecosystem and community
  • + Modular and composable
  • + Supports every major LLM provider
  • + Excellent documentation
  • + LangSmith for monitoring
  • + One API for 100+ providers
  • + Built-in load balancing and fallbacks
  • + Spend tracking and rate limiting
  • + OpenAI SDK compatible
Cons
  • Can be overly complex for simple tasks
  • Frequent breaking changes
  • Abstraction overhead
  • Steep learning curve
  • Adds a proxy layer (slight latency)
  • Complex config for advanced features
Tags
open-sourceframeworkpythonjavascriptragchains
api-gatewaymulti-providerproxyopen-source

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