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Tool Comparison

Semantic Kernel

Semantic Kernel

Microsoft's enterprise AI SDK — orchestrate LLMs in Python, C#, and Java.

Open Source
VS
DSPy

DSPy

Programming — not prompting — LLMs with auto-optimized, declarative modules.

Open Source
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At a Glance

AttributeSemantic KernelDSPy
License / PricingOpen SourceOpen Source
Typeaiai
GitHub Stars
Rating4.2/54.3/5
Key Features6 listed6 listed
Integrations5 listed5 listed
Categories
AI Agents
AI Agents

Key Features

Semantic Kernel

  • Plugins — wrap functions as AI-callable tools
  • Planner for autonomous goal decomposition
  • Memory store with vector DB integrations
  • Multi-LLM support: Azure OpenAI, OpenAI, Mistral, Ollama
  • Available in Python, C#, and Java
  • Native integration with Microsoft 365 and Azure

DSPy

  • Declarative signatures instead of brittle prompt strings
  • Automatic prompt optimization with teleprompters
  • Built-in evaluation and metric-driven tuning
  • Supports any LLM via OpenAI-compatible API
  • ChainOfThought, ReAct, and MultiChainComparison modules
  • Compiled programs that generalize across LLM versions

Real-World Use Cases

Semantic Kernel

Add AI to a .NET enterprise application

Add the Microsoft.SemanticKernel NuGet package

DSPy

Build a reliable multi-hop QA system

Define a Signature: 'question -> answer' with context field

Integrations

Semantic Kernel

openaianthropicazure-devopslangchainpinecone

DSPy

openaianthropicollamalangchainweaviate

🏆 Which should you choose?

Choose Semantic Kernel if…

  • you're already in the AI Agents ecosystem and prefer Semantic Kernel's workflow
Full Semantic Kernel guide →

Choose DSPy if…

  • you're already in the AI Agents ecosystem and prefer DSPy's workflow
Full DSPy guide →