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AI · head to head

AutoGen vs Semantic Kernel

AutoGen logo

AutoGen

AI

Programming framework for multi-agent agentic AI

From
Free
Rated
-
Full reviewWebsite
Semantic Kernel logo

Semantic Kernel

Machine Learning

Model-agnostic SDK for AI orchestration

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: AutoGen framework now in maintenance mode, no new features planned; Semantic Kernel steep learning curve for advanced features
  • They diverge on capability: AutoGen covers Multi-agent orchestration, Semantic Kernel covers Multi-model support.

Where they differ

Only the attributes on which AutoGen and Semantic Kernel actually diverge.

Attributes where AutoGen and Semantic Kernel differ
AttributeAutoGenSemantic Kernel
PlatformsPython, .NETPython, .NET, Java
CategoryAIMachine Learning

Identical on both: starting price (Free), pricing model (Open source, no pricing), free tier (Yes), user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in AutoGen

  • Multi-agent orchestration
  • Message passing API
  • AgentChat API
  • Extensions API
  • MCP server support
  • AutoGen Studio
  • Cross-language support
  • Observable agent networks

Only in Semantic Kernel

  • Multi-model support
  • Agent framework
  • Multi-agent systems
  • Plugin ecosystem
  • Vector database integration
  • Multimodal support
  • Local model support
  • Enterprise observability

What people use each for

The jobs each tool is most often brought in to do.

AutoGen

  • Building multi-agent conversational systemsnot Semantic Kernel
  • Rapid prototyping of agent applicationsnot Semantic Kernel
  • Research on agentic AI patterns and architecturesnot Semantic Kernel
  • Distributed agent networks across boundariesnot Semantic Kernel

Semantic Kernel

  • Building enterprise AI applications with LLM integrationnot AutoGen
  • Creating multi-agent systems for complex workflowsnot AutoGen
  • Developing AI-powered chatbots and assistantsnot AutoGen
  • Implementing RAG systems with vector databasesnot AutoGen

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

AutoGen

  • Framework now in maintenance mode, no new features planned
  • Steeper learning curve for advanced use cases
  • Microsoft recommends new projects use Agent Framework instead
  • Limited to Python and .NET platforms

Semantic Kernel

  • Steep learning curve for advanced features
  • Documentation focuses on Azure cloud services
  • Configuration complexity for multi-model scenarios
  • Requires understanding of AI/LLM concepts

Pricing, plan by plan

AutoGen

Free
  • Open SourceFree
    • MIT and CC-BY-4.0 licenses
    • Full framework access
    • Community support

Semantic Kernel

Free
  • Open SourceFree
    • MIT license
    • Full framework access
    • All language SDKs

Which should you pick?

Choose AutoGen if

  • You need multi-agent orchestration.
  • You want to start without paying.
  • You work on Python, .NET.
  • You also want message passing api.
AutoGen review

Choose Semantic Kernel if

  • You need multi-model support.
  • You want to start without paying.
  • You work on Python, .NET, Java.
  • You also want agent framework.
Semantic Kernel review

Questions people ask

Is AutoGen or Semantic Kernel better?
Neither clearly leads. AutoGen starts at Free and Semantic Kernel at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, AutoGen or Semantic Kernel?
AutoGen starts at Free and Semantic Kernel at Free.
Does AutoGen or Semantic Kernel run on more platforms?
AutoGen runs on Python, .NET. Semantic Kernel runs on Python, .NET, Java.
Can I use AutoGen for free?
Both have a free tier, so you can try either at no cost before committing.
What is AutoGen best used for?
AutoGen is most often used for building multi-agent conversational systems, rapid prototyping of agent applications, research on agentic ai patterns and architectures, distributed agent networks across boundaries. Of those, building multi-agent conversational systems and rapid prototyping of agent applications are not what Semantic Kernel is typically brought in for.
What can AutoGen do that Semantic Kernel cannot?
AutoGen covers Multi-agent orchestration, Message passing API, AgentChat API, Extensions API. Semantic Kernel covers Multi-model support, Agent framework, Multi-agent systems, Plugin ecosystem.

Answered from the vendors’ own pages

AutoGen: Is AutoGen still actively developed?

As of March 2026, AutoGen is in maintenance mode and will not receive new features. Microsoft recommends new projects use the Microsoft Agent Framework instead.

Source
Semantic Kernel: What LLM providers does Semantic Kernel support?

Semantic Kernel supports OpenAI, Azure OpenAI, Hugging Face, Nvidia, and other providers through extensible model implementations.

Source
AutoGen: Can I still use AutoGen for new projects?

While AutoGen is stable and maintained for existing projects, Microsoft recommends using the Microsoft Agent Framework for new development.

Source
Semantic Kernel: Can I run Semantic Kernel locally?

Yes. Semantic Kernel supports local models through Ollama, LMStudio, and ONNX for complete data control and offline operation.

Source
AutoGen: What LLM providers does AutoGen support?

AutoGen includes extensions for OpenAI and Azure OpenAI through its Extensions API, with community support for other providers.

Source
Semantic Kernel: Is Semantic Kernel free?

Yes. Semantic Kernel is MIT-licensed open source and completely free. You only pay for external LLM APIs you use.

Source
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