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Semantic Kernel vs LlamaIndex

Semantic KernelLlamaIndex

Bottom line: Semantic Kernel for enterprise .NET development teams; LlamaIndex for document-heavy RAG applications.

Semantic KernelSemantic Kernel

Microsoft's enterprise SDK for orchestrating LLMs, plugins, and agents.

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LlamaIndexLlamaIndex

Data framework for LLM apps and knowledge agents

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Votes00
PricingFreeFreemium
CategoryAgent FrameworksAi Agents
Tags
llm-frameworkagentsopen-sourcemicrosoftdotnet
llm-frameworkragdocument-parsingopen-sourceknowledge-agents
Best for
  • Enterprise .NET development teams
  • Microsoft/Azure-aligned organizations
  • Developers adding AI to existing apps
  • Document-heavy RAG applications
  • Enterprise knowledge agents
  • Teams needing reliable PDF parsing
Pros
  • First-class C#/.NET support, rare among AI frameworks
  • Free and open source
  • Enterprise features: type safety, DI, telemetry
  • Multi-language (C#, Python, Java)
  • Backed by Microsoft with clear Azure integration
  • Open-source frameworks are free (MIT)
  • Strong focus on retrieval and data quality
  • LlamaParse excels at complex document parsing
  • Managed LlamaCloud for production data workflows
  • Python and TypeScript support
Cons
  • Strategic focus shifting to Microsoft Agent Framework
  • Concepts like planners have changed across versions
  • Python support historically trailed .NET
  • Migration planning needed for long-term projects
  • Less multi-agent focus than AutoGen lineage
  • Overlaps with LangChain, adding decision fatigue
  • LlamaCloud credit costs scale with document complexity
  • Framework surface area has grown large
  • Fast-moving APIs can change between versions
  • Advanced agent features less mature than dedicated agent frameworks

Comparison generated from each tool's listing. Add or remove tools above to change it.