LlamaIndexvsLiteLLM

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

LlamaIndex

Data & ETL

Featured

Data framework for connecting LLMs to external data

Full review →Website ↗

LiteLLM

LLM APIs & Inference

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

Full review →Website ↗
FeatureLlamaIndexLiteLLM
CategoryData & ETLLLM APIs & Inference
PricingFree (open-source) + CloudFree (open-source), hosted proxy available
GitHub Stars
✓ More stars
38k
16k
PlatformsLinux, macOS, WindowsLinux, macOS, Docker
Key Features
  • ✓ RAG pipelines
  • ✓ Data connectors
  • ✓ Indexing
  • ✓ Query engine
  • ✓ Agent tools
  • ✓ 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
  • + Best-in-class RAG framework
  • + 100+ data connectors
  • + Multiple index types
  • + Great documentation
  • + Active community
  • + One API for 100+ providers
  • + Built-in load balancing and fallbacks
  • + Spend tracking and rate limiting
  • + OpenAI SDK compatible
Cons
  • − Can be complex for simple use cases
  • − Abstractions hide complexity
  • − Learning curve for advanced features
  • − Some features require LlamaCloud
  • − Adds a proxy layer (slight latency)
  • − Complex config for advanced features
Tags
ragdataindexingopen-source
api-gatewaymulti-providerproxyopen-source

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