SciSharp/LLamaSharp

Health v2 · maintenance only

Adoption not part of the score

3787 stars · 506 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

LLamaSharp is a cross-platform C#/.NET library that wraps llama.cpp to run LLaMA-family and other LLMs (including multimodal LLaVA) efficiently on local devices with CPU, CUDA, or Vulkan backends. It provides high-level APIs, chat sessions, and RAG support for deploying LLMs in .NET applications.

Use cases

• run llama models locally in a C# app
• run LLM inference on device with .NET
• build a chatbot in C# with a local LLM
• run LLaVA multimodal model in .NET
• integrate local LLM with Semantic Kernel
• do RAG with a local LLM in .NET
• run LLM on GPU with CUDA from C#

When to choose

• you are building a .NET/C# application that needs local LLM inference
• you want llama.cpp performance without writing C++ or managing native bindings yourself
• you need CPU, CUDA, or Vulkan backend flexibility on cross-platform targets
• you want high-level chat, RAG, and Semantic Kernel integration out of the box

When to avoid

• your stack is Python, Node.js, or another non-.NET ecosystem
• you need to serve many concurrent users at scale rather than local/on-device inference
• you need models or features not supported by llama.cpp
• you want a managed pure-C# inference engine without native binaries

Facets

library · maturity active

llm-inference rag chatbot sdk large-language-models artificial-intelligence machine-learning chatbots cross-platform windows llamacpp dotnet csharp local-inference llava multimodal semantic-kernel retrieval-augmented-generation linux macos gpu

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