Llama Stack vs Semantic Kernel
Updated March 10, 2026
Overview
Llama Stack is Meta's standardized API and SDK for building AI applications on top of Llama models. It provides a unified interface for inference, safety, memory, and agentic workflows — with swappable providers for local, cloud, and on-device deployment. As the official framework for the Llama ecosystem, it is becoming the default for teams building on open-source Llama models.
Semantic Kernel is Microsoft's enterprise SDK for integrating AI into applications. It provides planners for multi-step task execution, plugin architectures for tool use, memory systems, and connectors for all major LLM providers. Available in C#, Python, and Java, Semantic Kernel is designed for enterprise .NET shops building AI-powered features into existing applications.
Key features
Core capabilities each platform advertises.
- Enterprise AI orchestration by Microsoft
- C# and Python SDKs
- Plugin architecture for tools
- Memory and planning capabilities
- Azure and Microsoft 365 integration
Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- Completely free and open-source framework with permissive licensing
- Unified APIs across multiple service providers simplify deployment
- Recent 50 percent pricing reductions make models more cost-effective
- Strong backing from Meta with partnerships across major tech companies
Cons
- Setup and configuration complexity with build failures reported
- Documentation gaps lead to import errors and confusion
- Windows compatibility issues limit platform support
- Lack of security policies may concern enterprise users
Pros
- Free open-source
- Microsoft-backed
- Multi-language
Cons
- Learning curve
- Microsoft focus
Llama Stack or Semantic Kernel — which should you choose?
Choose Llama Stack if you wantChoose if you want
Choose Semantic Kernel if you wantChoose if you want
- Enterprise AI on Microsoft stack
- Copilot-style applications
- Integrating AI into .NET applications
- Microsoft 365 automation
- Enterprise workflow orchestration
Compare Llama Stack and Semantic Kernel on your own traffic
Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 500+ models through one gateway.
