12 alternatives to Semantic Kernel that we cover: AutoGen, LangChain, LlamaIndex, Langflow, Botpress, Gumloop, Lindy, Microsoft Copilot Studio, Pydantic AI, Relevance AI, Voiceflow, LangGraph. The table shows the evidence behind each entry and whether its pricing has been verified.
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Microsoft's model-agnostic SDK for building AI agents; its README calls Microsoft Agent Framework the enterprise-ready successor.
The Semantic Kernel README says Microsoft Agent Framework (MAF) is the enterprise-ready successor and is at version 1.0 with stable APIs. The repository is still MIT-licensed and active, with python-1.45.0 released Oct 6, 2026.
What it does well: MIT license; Multi-language.
Where it falls short: Successor product exists; Our own run only partly worked: Semantic Kernel 1.45.0 returned an empty reply with our standard prompt (0 of 3) but worked once the prompt used its plugin-prefixed tool name (3 of 3); a naming trap with small models. See /tests/semantic-kernel.
Latest version we cover: python-1.45.0 (Oct 6, 2026). Vendor: Microsoft.
When to look beyond Semantic Kernel
Skip Semantic Kernel if:
You are starting new agent work and want Microsoft's recommended path (Agent Framework)
Tested (smoke test, 2026-10-25, local 3B model (Qwen2.5-3B))
Not verified
1.2.17
Evidence labels: Reported means written from official sources; Tested means a small smoke test with its scope stated. See methodology. Pricing status shows how well we could verify prices; open each tool page for the note.
Verdict: Microsoft's open-source multi-agent framework; its README now says the project is in maintenance mode and points to Microsoft Agent Framework.
Pick AutoGen if: Existing AutoGen projects that need reference material; Researchers studying multi-agent patterns.
For agent building: neither AutoGen nor Semantic Kernel has an editorial rank in this category.
Pricing model: AutoGen is Free and open source; Semantic Kernel is Free and open source.
Free tier: AutoGen: Free to self-host. Semantic Kernel: Free to self-host.
Runs on: AutoGen: Python and .NET. Semantic Kernel: .NET, Python and Java.
License: AutoGen: MIT (code) and CC-BY-4.0 (docs), per GitHub. Semantic Kernel: MIT (per GitHub).
Verdict: A dependable foundation for stateful agents; this release is a routine fix, so only update if the RemoteGraph or recursion fixes affect you.
Pick LangGraph if: Developers who want explicit control over agent state and flow; Teams running long-lived, resumable agents.
For agent building: LangGraph is #3, Semantic Kernel is not ranked.
Latest release we cover: LangGraph 1.2.17 on Oct 24, 2026. Semantic Kernel python-1.45.0 on Oct 6, 2026.
Evidence: LangGraph: Tested (smoke test, 2026-10-25, local 3B model (Qwen2.5-3B)). Semantic Kernel: Reported (not run by us).
Strength: LangGraph: MIT license, large community. Semantic Kernel: MIT license.
Main caveat: LangGraph: More concepts to learn than simpler SDKs. Semantic Kernel: Successor product exists.
FAQ
What are the best alternatives to Semantic Kernel?
AutoGen, LangChain, LlamaIndex, Langflow, Botpress, Gumloop, Lindy, Microsoft Copilot Studio, Pydantic AI, Relevance AI, Voiceflow, LangGraph. Each is covered with a verdict on this site.
When should I use something other than Semantic Kernel?
Skip Semantic Kernel if: You are starting new agent work and want Microsoft's recommended path (Agent Framework).
