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ggml avatar

ggml

Dependency-free C/C++ tensor library for running ML models anywhere

  • AI models and runtimes
  • Languages and frameworks
View on GitHub
Website

What it is

A tensor library written in plain C and C++ with no external dependencies, used as the compute core behind llama.cpp and whisper.cpp. Its kernels are hand-optimized with SIMD on ARM, x86, and RISC-V processors, it runs on CPU, GPU, NPU, and WebAssembly backends, and it supports quantization from 2 to 8 bits plus the GGUF format for storing models. Developers building inference engines or embedding models into native apps use it to run neural networks efficiently on ordinary hardware without allocating memory at runtime.

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Facts

Stars
15,513 GitHub stars.
15,513

Forks
1,880
Commits
4,998
Contributors
500+
Language
C++
License
MIT
Last commit
Oct 20, 2026
On GitHub since
September 2022
First release
September 2025
Platforms
library
Self-hostable
No
Tags
  • machine-learning
  • llm-inference
  • local-ai
  • model-optimization
  • gpu-computing

Last synced from GitHub on Oct 20, 2026

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What people are saying

Updated Oct 21, 2026
  • Bluesky“Ever wanted to run ML models on your own hardware, no bulky dependencies? That's the promise behind ggml. It makes me wonder: what new applications could we…”Nov 17, 2025 · 0 likes · 0 replies (opens Bluesky in a new tab)