What it does
Core capabilities at a glance
- Multi-language (C#, Python, Java)
- Planner for automatic function orchestration
- Semantic and native function composition
- Memory and vector store connectors
- Azure OpenAI and OpenAI integration
- Enterprise-grade with .NET ecosystem
Deep dive
The full breakdown - performance, comparisons, and setup
Semantic Kernel
Semantic Kernel is Microsoft's answer to LangChain, designed primarily for the .NET ecosystem but supporting Python and Java as well.
What it is
Semantic Kernel is an SDK that bridges LLMs with conventional programming. It introduces concepts like plugins (functions the LLM can call), planners (automatic orchestration), and memories (vector storage).
Get started
// C#
using Microsoft.SemanticKernel;
var kernel = Kernel.CreateBuilder()
.AddOllamaChatCompletion("qwen3:30b")
.Build();
var result = await kernel.InvokePromptAsync("Hello!");When to use something else
From the community
What users are saying
“I'm using Semantic Kernel to build more complex AI systems. The technology is still maturing and you deal with things like missing abstractions and the like. The planners are intriguing and promising, and they'll be more manageable once assistants are available to make things more modular.”
“Hi, article author here, Semantic Kernel and LangChain are both geared towards NLP but they have different takes on it. While LangChain revolves around creating sequences of calls known as "Chains", SK employs a "Kernel" to manage these sequences and has a "Planner" to auto-create chains for new user needs.”
“We are .NET shop (server side at least), so the opportunity to find something that works with .NET was a huge plus for us. I heard similar comments made by Java developers, in regards to SK for Java. I have been following Semantic Kernel since April and I have been focused on Kernel Memory recently.”
Frequently asked
Quick answers to common questions
What is Semantic Kernel?
Semantic Kernel is a agent-framework tool for local AI workloads. Microsoft's SDK for integrating LLMs with C#, Python, and Java - enterprise-grade AI orchestration.
Is Semantic Kernel free and open source?
Yes, Semantic Kernel has 28,671 GitHub stars and is licensed under MIT. You can self-host it for free on linux, macos, windows.
What platforms does Semantic Kernel support?
Semantic Kernel runs on linux, macos, windows.
What hardware do I need for Semantic Kernel?
The hardware requirements depend on which models you run. Check our hardware directory for compatible GPUs and systems. Semantic Kernel has 28,671 GitHub stars and an active community.
Does Semantic Kernel support GPU acceleration?
Semantic Kernel supports GPU acceleration via CUDA, Metal, or Vulkan depending on your platform. For the best performance, pair it with an NVIDIA RTX 4090 or 5090.
What are the best alternatives to Semantic Kernel?
Popular alternatives include other agent-framework tools in our directory. Browse our full collection at /tool for comparisons, community reviews, and benchmark data to find the right fit for your workflow.
How much does Semantic Kernel cost?
Semantic Kernel is free-open-source. It is completely free and open source to self-host.
Pairs well with
Complementary tools, models, and hardware