Today for AI
ALL INTELLIGENCE
llama.cpp and ggml Reach 1.0 Milestone ReleasesHacker News AIT2·Open Source

ggml Ships v1.0.0 as Dependency-Free Tensor Library

Original title: Ggml v1.0.0
58AI Score

ggml has released v1.0.0, marking the first formal versioned milestone for the tensor library underpinning the llama.cpp ecosystem. Its core value is a dependency-free C/C++ implementation spanning x86, ARM, RISC-V and more, with 2- to 8-bit integer quantization plus MXFP4 and NVFP4 microscaling formats and zero runtime memory allocation. For local-inference and edge-deployment developers, this signals long-term ecosystem stability.

Related Entities

TERMGGUFTOOLggmlTOOLllama.cppTERMMXFP4TERMNVFP4

Full Report

Contents3 sections

ggml

Tensor library for machine learning

Quick start

Build from source:

BASH
git clone https://github.com/ggml-org/ggml
cd ggml

mkdir build && cd build
cmake ..
cmake --build . --config Release -j 8

For a minimal, fully commented example (matrix multiplication), see examples/simple.

Description

The main goal of ggml is to be a simple, portable, and efficient tensor library for machine learning with minimal setup.

  • Plain C/C++ implementation without any dependencies
  • Cross-platform - x86, ARM, RISC-V, LoongArch, PowerPC, s390x, and WebAssembly
  • SIMD-optimized kernels for x86, ARM, and RISC-V
  • Broad backend support - CPU, GPU, NPU, and browser
  • 2- to 8-bit integer quantization, plus MXFP4 and NVFP4 microscaling formats
  • Zero memory allocations during runtime

Documentation