LangGraph vs Semantic Kernel

Side-by-side comparison of features, pricing, and ratings

Analysis generated Live tool data as of 2026-11-13
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LangGraph or Semantic Kernel: which should you choose?

DimensionLangGraphSemantic Kernel
PricingFree · from $39/seat/moFree
Best forBackend and platform engineers shipping stateful agents to production, Teams that need human approval gates inside an agent loop.NET developers building copilots and AI agents, Enterprise teams standardized on Microsoft Azure
Standout featuresGraph-based state management for explicit agent control flow · Human-in-the-loop checks to steer and approve agent actions · Built-in memory storing conversation history and context across sessionsPlugin-based composition of reusable functions · Memory layer for supplying context to models · Process Framework for stateful, durable workflows
Viability score81/10073/100
APIYesYes

LangGraph is the stronger pick for backend and platform engineers shipping stateful agents to production; Semantic Kernel fits better for .net developers building copilots and ai agents.

Built from live tool data, last verified 2026-11-13.

LangGraph
LangGraph

LangGraph is a low-level agent orchestration framework for building stateful, controllable AI agents as graphs.

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Semantic Kernel
Semantic Kernel

Microsoft's open-source SDK for building AI agents and copilots with plugins, memory, and multi-agent orchestration.

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Pricing
Freemium
Free
Plans
DeveloperFree
Plus$39/seat/mo
EnterpriseCustom
Open SourceFree
Popularity
3.1k views
3.0k views
Skill Level
Advanced
Intermediate
API Available
Platforms
API
API
Categories
🕸️ Agent Frameworks & Orchestration📡 LLM Observability & Evals
🕸️ Agent Frameworks & Orchestration
FeaturesLangGraphSemantic Kernel
Graph-based state management for explicit agent control flow
Human-in-the-loop checks to steer and approve agent actions
Built-in memory storing conversation history and context across sessions
First-class token-by-token streaming of reasoning and actions
Single-agent, multi-agent, and hierarchical architectures in one framework
Low-level primitives for fully customizable agent design
Model-agnostic: build and ship with any model provider
MCP support in the open-source stack, including elicitation and the stateless protocol
Agent runtime for orchestrating long-running agent workflows
MIT-licensed open-source library, free to use
Plugin-based composition of reusable functions
Memory layer for supplying context to models
Process Framework for stateful, durable workflows
Agent Framework for multi-agent coordination
Group chat pattern for multi-agent systems
Security filters for AI policy enforcement
Observability and telemetry hooks
Multi-language SDK support (C#, Python, Java)
Azure OpenAI connectivity
OpenAI connectivity
Microsoft 365 Copilot extension
Microsoft Graph data access
Kernel extensibility through middleware
Semantic functions and plans
Connectors for external data sources
IntegrationsLangGraphSemantic Kernel
OpenAI
Anthropic
Google Gemini
OpenRouter
Fireworks
Baseten
Ollama
Azure
AWS Bedrock
HuggingFace
Azure OpenAI
Microsoft 365 Copilot
Microsoft Graph
Azure Cognitive Search
Entity Framework
ASP.NET Core
Blazor
Power Platform
Microsoft Entra ID

Frequently Asked Questions

Which is better, LangGraph or Semantic Kernel?

The best choice between LangGraph and Semantic Kernel depends on your specific use case — we compare them independently on features, current pricing, integrations, and real-world signals (with an on-demand sentiment scan available for each). See the side-by-side breakdown above to match them to your needs.

What are the main differences between LangGraph and Semantic Kernel?

The key differences include pricing model, feature set, platform support, and skill level requirements. Review the full comparison on RightAIChoice for a detailed breakdown.

Is there a free version of LangGraph or Semantic Kernel?

Check the pricing section in the comparison for the latest pricing details on both tools, including free tiers, trial options, and paid plans.

What else are LangGraph and Semantic Kernel compared with?

Where can you read more about LangGraph and Semantic Kernel?

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Analysis generated by our model pipeline from live data: