LangChain vs 
Semantic Kernel
LangChain vs Semantic Kernel compared for 2026 — features, license, ease of use, performance and which one to choose. Compose chains, tools and agents vs Microsoft's enterprise agent framework.
Updated regularly · curated by OpenSourceAI.tech
LangChain vs Semantic Kernel at a glance
| Spec | LangChain | Semantic Kernel |
|---|---|---|
| Category | LLM / RAG framework | LLM / RAG framework |
| Type | LLM app framework | LLM orchestration SDK |
| License | MIT | MIT |
| Runs locally | Cloud-optional | Partial |
| Primary language | Python / JS | C#/Python |
| Ease of use | Intermediate | Intermediate |
| Best for | developers building tool-using LLM apps | enterprise teams on the Microsoft stack |
| GitHub stars | 141.9k | 28.3k |
Feature comparison
| Feature | LangChain | Semantic Kernel |
|---|---|---|
| Python | ✓ | ✓ |
| JavaScript / TS | ✓ | ✗ |
| Agents | ✓ | ✓ |
| RAG | ✓ | ✓ |
| Streaming | ✓ | ✓ |
| Many integrations | ✓ | ✓ |
How LangChain and Semantic Kernel score
| Criterion | LangChain | Semantic Kernel |
|---|---|---|
| Popularity | 5.0 | 3.5 |
| Maintenance | 5.0 | 5.0 |
| Ease of use | 3.5 | 3.5 |
| Privacy | 3.5 | 3.5 |
| License freedom | 5.0 | 5.0 |
Scores are computed automatically from public signals — GitHub stars (popularity), recent commit activity (maintenance), license type (freedom), local-first design (privacy) and onboarding complexity (ease of use). Indicative, not a verdict.
What each one is
LangChain
LangChain is a framework for building LLM applications by composing prompts, models, tools, memory and agents, with a vast ecosystem of integrations.
- Huge ecosystem of integrations
- Building blocks for chains, tools and agents
- Python and JavaScript support
Semantic Kernel
Semantic Kernel is Microsoft's open SDK for building AI agents and orchestrating models in .NET, Python and Java, with plugins, planners and enterprise-grade patterns.
- First-class .NET, Python and Java support
- Enterprise patterns: planners, plugins, filters
- Backed and used by Microsoft at scale
Key differences
LangChain is lLM app framework, while Semantic Kernel is lLM orchestration SDK. They also differ in how they run (Cloud-optional vs Partial). In short, LangChain fits developers building tool-using LLM apps, and Semantic Kernel fits enterprise teams on the Microsoft stack.
Which should you choose?
Choose LangChain for developers building tool-using LLM apps. Choose Semantic Kernel for enterprise teams on the Microsoft stack.
There is rarely one winner — many setups use both. The right pick depends on your hardware, your team's skills, and whether you value simplicity or control.
Frequently asked questions
Is LangChain or Semantic Kernel easier to use?
Both sit at a similar level (Intermediate). Your choice should come down to fit rather than difficulty.
Are LangChain and Semantic Kernel free?
LangChain is free and open source (MIT), and Semantic Kernel is free and open source (MIT). Neither charges for the core software.
Can I run LangChain and Semantic Kernel locally?
LangChain: cloud-optional · Semantic Kernel: partial. Both can be used without sending your data to a third-party cloud where their setup allows.
LangChain vs Semantic Kernel — which should I pick in 2026?
Choose LangChain for developers building tool-using LLM apps. Choose Semantic Kernel for enterprise teams on the Microsoft stack.
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