Show HN: TensorSharp: Open-Source Local LLM Inference Engine (tensorsharp.ai)

TensorSharp has launched as an open-source local inference engine for large language models (LLMs), enabling users to run AI applications entirely on their own hardware without data privacy concerns or per-token fees. The engine supports various architectures like Gemma and GPT-OSS and can seamlessly integrate into .NET applications. Users can quickly get started with just a few commands, leveraging a command-line interface or a web UI for hosting chatbots and APIs, making it accessible for developers at all skill levels. This development is significant for the AI/ML community as it promotes privacy and flexibility in deploying AI models, allowing for local processing that eliminates dependency on external servers and their associated costs. TensorSharp's compatibility with existing tools via standard API formats ensures that it can cater to engineers looking for efficient solutions without having to extensively modify their workflows. Benchmarks demonstrate that TensorSharp can compete with established C++ engines, providing a strong alternative for those seeking fast, customizable LLM deployment options across various hardware platforms, including NVIDIA, AMD, and Apple Silicon.