LangGraph vs Semantic Kernel
Side-by-side comparison of features, pricing, and ratings
At a glance
| Dimension | LangGraph | Semantic Kernel |
|---|---|---|
| Pricing | freemium · from Developer $0/seat per month | free · from Open Source $0/mo |
| Best for | Backend and platform engineers building production agents, Teams needing fine-grained control over agent workflows | .NET developers building copilots and AI agents, Enterprise teams on Microsoft Azure |
| Standout features | Graph-based state management for agent control flow · Human-in-the-loop checkpoints to steer and approve agent actions · Built-in memory storing conversation histories across sessions | Plugin-based skill composition · Memory management for context · Process Framework for stateful workflows |
| Viability score | 81/100 | 73/100 |
| API | Yes | Yes |
LangGraph is the stronger pick for backend and platform engineers building production agents; Semantic Kernel fits better for .net developers building copilots and ai agents.
Built from live tool data, last verified 2026-09-29.
MIT-licensed agent runtime and low-level orchestration framework for building reliable, stateful AI agents.
Visit Website
Microsoft's open-source SDK for building production-grade AI agents with plugins, memory, and orchestration.
Visit WebsiteWhat real users say: LangGraph vs Semantic Kernel
Not marketing copy and not our opinion — a structured sweep of public discussion (reviews, forums, communities and video comments), showing what people praise and what they complain about for each tool.
LangGraph
117 mentions across 6 sources · 53% positive — mixed (averaged across 6 sources)
Hacker News, YouTube, Bluesky, Stack Overflow, GitHub, Lemmy
What users praise
- • Fine-grained control over agent workflows and state transitions.
- • Excellent for building complex multi-agent and hierarchical systems.
- • Human-in-the-loop checks provide reliable agent moderation.
- • Graph-based orchestration makes deterministic workflows intuitive.
What frustrates them
- • Steep learning curve and API confusion for new users.
- • Gets complicated fast for simple or single-agent tasks.
- • Long tool calls silently re-execute on cloud, wasting cost.
- • Security vulnerabilities can expose files and secrets.
Researched Jul 25, 2026
Semantic Kernel
62 mentions across 5 sources · 45% positive — mixed (averaged across 5 sources)
Hacker News, YouTube, Stack Overflow, GitHub, Lemmy
What users praise
- • Deep integration with Azure OpenAI and Microsoft Graph for enterprise.
- • Mature plugin system for composable, production-grade AI agents.
- • Multi-language support: C#, Python, Java covers diverse teams.
- • Process framework for stateful, durable workflows beyond simple chains.
What frustrates them
- • Steep learning curve, especially for beginners new to agent concepts.
- • Documentation is scattered and sometimes outdated, leading to confusion.
- • Frequent API changes cause friction and require constant maintenance.
- • MCP tool integration is buggy and not reliably followed.
Researched Aug 15, 2026
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.
More LangGraph or Semantic Kernel comparisons
Explore each tool further
Browse these categories
One email a week — new tools, honest comparisons, no spam.
Last reviewed: May 12, 2026