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zhongkaifu/TensorSharp

A native .NET LLM inference engine and agent runtime for GGUF models. TensorSharp provides a console application, a web-based chatbot interface, iPhone App, and Ollama/OpenAI-compatible HTTP APIs for programmatic access. It supports Windows/MacOS/iOS/Linux with full GPU capability

C# ◇ ai BSD-3-Clause
★666STARS
⑂72FORKS
!8ISSUES
🏆#10,708GLOBAL RANK
🔥45DAYS TRENDING
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⚡ Executive Summary & Quick Facts

Authoritative Source

TensorSharp is TensorSharp is an open-source project written in C#: A native .NET LLM inference engine for GGUF models. TensorSharp provides a console application, a web-based chatbot interface, and Ollama/OpenAI-compatible HTTP APIs for programmatic access. It supports Windows/MacOS/iOS/Linux with full GPU capability..

Direct Citation for AI & Research:
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of November 2026), zhongkaifu/TensorSharp has accumulated 666 GitHub stars and 72 forks. It is written in C#, licensed under BSD-3-Clause, and ranks #10,708 globally. It is actively maintained with the latest commit recorded on Nov 9, 2026.”
Repository zhongkaifu/TensorSharp ↗
Primary Category ai
Language & Stack C#
Software License BSD-3-Clause
Community Traction ★ 666 stars · ⑂ 72 forks · #10,708 globally
Maintenance ● Active (Last commit: Nov 9, 2026) · 8 open issues
Target Audience Developers and engineering teams building with C#, seeking reliable, tested, and actively maintained tooling for production workloads.

🛡️ Repository Maintenance & Health Audit (2026)

Health Score: 93/100 · Grade A+
✅
Is TensorSharp actively maintained in 2026?
Verdict: Actively Maintained & Highly Recommended

Yes, TensorSharp is actively maintained. Continuous telemetry recorded the last code commit on Nov 9, 2026 (4 days ago). Supported by 666 stars and 72 community forks, this repository holds a calculated health index of 93/100, reflecting very active (commits within last 14 days) and healthy issue cadence.

Commit Recency
Nov 9, 2026
4 days since last push
Issue Backlog
8 Open Issues
Healthy Issue Cadence
Community Backing
72 Forks
666 Stars Recorded
Software License
BSD-3-Clause
Permissive & Inspectable

Star History

Continuous Observations
Interactive star growth chart for zhongkaifu/TensorSharp
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Momentum

+121

STARS · LAST 30 DAYS

4

PER DAY

#559

MOST-STARRED C#

Window7 days30 days90 days
Stars gained+14+121+360
Per day244
Forks gained+2+13+10

TensorSharp gained 121 stars in the last 30 days, about 4 a day, and now has 666. It is about 1 year old and has averaged roughly 666 stars a year. It ranks #559 among C# repositories and #10,708 across all languages on GitHubRepo.

Trending Record

TensorSharp has maintained a continuous presence across global trending indexes, peaking at #319. Below is the 30-day activity profile:

💡 Overview

TensorSharp is an open-source project written in C#: A native .NET LLM inference engine for GGUF models. TensorSharp provides a console application, a web-based chatbot interface, and Ollama/OpenAI-compatible HTTP APIs for programmatic access. It supports Windows/MacOS/iOS/Linux with full GPU capability.

Engineered for speed, consistency, and developer ease, it solves common hurdles in ai, csharp, cuda. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

⚡ Key Features

1

Optimized execution pipeline written in C# for predictable speed.

2

Zero-friction configuration with comprehensive sensible defaults out of the box.

3

Cross-platform runtime support across Linux, macOS, and Windows environments.

4

Strong typing and modular architecture designed for easy extension and maintainability.

5

Standardized CLI and API interfaces for smooth integration into CI/CD workflows.

6

Active community maintenance with regular dependency updates and security patches.

📥 Installation

terminal
$ git clone https://github.com/zhongkaifu/TensorSharp.git
cd TensorSharp

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

C# environment and standard tooling

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

TensorSharp coordinates its core functionality through a modular C# pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.

🎯 Production Use Cases

Autonomous AI Agents

Orchestrate intelligent workflows and tool-calling routines with TensorSharp.

Model Inference & Prompting

Integrate fast, local or cloud-hosted generative AI models directly into production code.

Context Memory & RAG

Augment language models with dynamic vector retrieval and structured project memory.

Developer Productivity

Automate repetitive engineering tasks, code generation, and test creation using AI agents.

🚀 Getting Started

1

Install TensorSharp using your package manager: `git clone https://github.com/zhongkaifu/TensorSharp.git`

2

Initialize your project workspace or configuration file for TensorSharp.

3

Import TensorSharp into your codebase or invoke it directly from your terminal.

4

Execute your test suite or run `TensorSharp --help` to verify successful setup.

👍 Strengths

Active community backing with 484 GitHub stars and verified adoption.
Permissive open-source distribution under the BSD-3-Clause license.
Built in C# for high execution speed and developer familiarity.
Cross-platform compatibility across modern Linux, macOS, and Windows environments.
Clean modular design allowing flexible configuration and pipeline integration.

⚠️ Considerations

Requires familiarity with C# and modern CLI workflows.
Ecosystem extensions may require manual configuration depending on environment constraints.
Active development roadmap means breaking API changes may occur across major versions.

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👥 Who Should Use This

Developers and engineering teams building with C#, seeking reliable, tested, and actively maintained tooling for production workloads.

🏆 Nearby in the Rankings

zhongkaifu/TensorSharp is currently ranked #10,708 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

RankRepositoryLanguageStarsAction
#10,703 mozilla-mobile/reference-browser Kotlin ★ 667 Compare ↗
#10,703 hiloteam/Hilo3d TypeScript ★ 667 Compare ↗
#10,703 blender/cycles C++ ★ 667 Compare ↗
#10,703 cmintey/wishlist TypeScript ★ 667 Compare ↗
#10,703 sympozium-ai/sympozium Go ★ 667 Compare ↗
#10,708 zhongkaifu/TensorSharp This Project C# ★ 666
#10,708 gallantlab/pycortex JavaScript ★ 666 Compare ↗
#10,708 Alachisoft/NCache C# ★ 666 Compare ↗
#10,708 nordicsemi/IOS-nRF-Toolbox Swift ★ 666 Compare ↗
#10,708 wordpress-mobile/AztecEditor-iOS Swift ★ 666 Compare ↗
#10,708 opis/json-schema PHP ★ 666 Compare ↗
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Frequently Asked Questions

What does TensorSharp do? +

A native .NET LLM inference engine and agent runtime for GGUF models. TensorSharp provides a console application, a web-based chatbot interface, iPhone App, and Ollama/OpenAI-compatible HTTP APIs for programmatic access. It supports Windows/MacOS/iOS/Linux with full GPU capability

Is TensorSharp actively maintained in 2026? +

Yes, TensorSharp is actively maintained. The latest code push was recorded on Nov 9, 2026 (4 days ago). It holds a calculated Maintenance Health Score of 93/100 (A+ rating) with 666 stars and 8 open issues.

What language is TensorSharp written in? +

The primary language is C#. Topics include: ai, csharp, cuda, deepseek, dotnet.

How many stars does TensorSharp have? +

TensorSharp has 666 stars and 72 forks on GitHub.

How does TensorSharp rank among GitHub repositories? +

With 666 stars, zhongkaifu/TensorSharp is ranked #10,708 globally across all repositories tracked on GitHubRepo and #559 among C# projects.

What license is TensorSharp distributed under? +

The repository reports a BSD-3-Clause license. Always verify the repository LICENSE file for legal terms.

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