# ggml

Published articles for ggml.

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## Security updates for Friday

DevFeed: [Security updates for Friday](<https://devfeed.tech/articles/security-updates-for-friday-8503.md>)

Original publisher: [Read original article](<https://lwn.net/Articles/1093765/>)

Author: jzb

Published: 2026-09-11T13:14:32Z

Content type: news

Language: en

Sources: [LWN.net](<https://devfeed.tech/sources/lwn-net.md>)

Topics: [Debian](<https://devfeed.tech/topics/debian.md>), [cURL](<https://devfeed.tech/topics/curl.md>), [Azure](<https://devfeed.tech/topics/azure.md>)

Tags: [azure](<https://devfeed.tech/tags/azure.md>), [debian](<https://devfeed.tech/tags/debian.md>), [ggml](<https://devfeed.tech/tags/ggml.md>), [kernel](<https://devfeed.tech/tags/kernel.md>), [linux](<https://devfeed.tech/tags/linux.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [oracle](<https://devfeed.tech/tags/oracle.md>), [python](<https://devfeed.tech/tags/python.md>), [ruby](<https://devfeed.tech/tags/ruby.md>), [security](<https://devfeed.tech/tags/security.md>), [updates](<https://devfeed.tech/tags/updates.md>)

### AI overview

Security updates have been issued across AlmaLinux, Debian, Fedora, Oracle, Red Hat, SUSE, and Ubuntu for a broad set of system libraries, tools, runtimes, and applications.

### Source excerpt

Security updates have been issued by AlmaLinux (apr-util and qt6-qt5compat), Debian (libevent and ruby-rack), Fedora (bluez, corosync, curl, dokuwiki, grpcurl, libevent, and rest), Oracle (gstreamer1-plugins-bad-free, perl-DBI, python-urllib3, qt5-qtbase, qt6-qt5compat, and thunderbird), Red Hat (osbuild-composer), SUSE (azure-storage-azcopy, chromedriver, corosync, ggml-devel, helm, kernel, libmariadb-devel, libzypp, zypper, opensc, php7, tomcat10, and waylyrics), and Ubuntu (apache2, beets, glibc, kissfft, libebml, linux-nvidia-6.17, php8.1, php8.3, php8.5, and python2.7, python3.4, python3.5, python3.6, python3.7, python3.8, python3.9, python3.10, python3.11, python3.12, python3.14).

## Local LLM Inference : llama.cpp, GGUF, Quantizations and GGML Explained

DevFeed: [Local LLM Inference : llama.cpp, GGUF, Quantizations and GGML Explained](<https://devfeed.tech/articles/local-llm-inference-llama-cpp-gguf-quantizations-and-ggml-explained-35012.md>)

Original publisher: [Read original article](<https://read.theaimerge.com/p/an-ai-engineers-guide-to-running>)

Author: Alex Razvant

Published: 2026-03-03T11:31:04Z

Content type: tutorial

Language: en

Sources: [Neural Bits](<https://devfeed.tech/sources/neural-bits.md>)

Topics: [llama.cpp](<https://devfeed.tech/topics/llama-cpp.md>), [ggml](<https://devfeed.tech/topics/ggml.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Local AI](<https://devfeed.tech/topics/local-ai.md>), [quantization](<https://devfeed.tech/topics/quantization.md>)

Tags: [backend](<https://devfeed.tech/tags/backend.md>), [cross-platform](<https://devfeed.tech/tags/cross-platform.md>), [efficiently](<https://devfeed.tech/tags/efficiently.md>), [embedded](<https://devfeed.tech/tags/embedded.md>), [format](<https://devfeed.tech/tags/format.md>), [ggml](<https://devfeed.tech/tags/ggml.md>), [inference](<https://devfeed.tech/tags/inference.md>), [llama-cpp](<https://devfeed.tech/tags/llama-cpp.md>), [llm](<https://devfeed.tech/tags/llm.md>), [local-llm](<https://devfeed.tech/tags/local-llm.md>), [model](<https://devfeed.tech/tags/model.md>)

### AI overview

A practical guide to local LLM inference with llama.cpp, explaining how the GGUF model format, GGML backend concepts, quantization, and inference workflows fit together for efficient execution on edge devices.

### Source excerpt

Learn how the llama.cpp runtime, GGML backend concepts, and GGUF model format fit together for fast local inference across devices.

## GGML and llama.cpp join HF to ensure the long-term progress of Local AI

DevFeed: [GGML and llama.cpp join HF to ensure the long-term progress of Local AI](<https://devfeed.tech/articles/ggml-and-llama-cpp-join-hf-to-ensure-the-long-term-progress-of-local-ai-7215.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/ggml-joins-hf>)

Author: Georgi Gerganov; Xuan-Son Nguyen; Aleksander Grygier; Lysandre; Victor Mustar; Julien Chaumond

Published: 2026-02-20T00:00:00Z

Content type: news

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [llama.cpp](<https://devfeed.tech/topics/llama-cpp.md>), [Local AI](<https://devfeed.tech/topics/local-ai.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [model-deployment](<https://devfeed.tech/topics/model-deployment.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [User Experience](<https://devfeed.tech/topics/user-experience.md>)

Tags: [community](<https://devfeed.tech/tags/community.md>), [devices](<https://devfeed.tech/tags/devices.md>), [ggml](<https://devfeed.tech/tags/ggml.md>), [inference](<https://devfeed.tech/tags/inference.md>), [llama-cpp](<https://devfeed.tech/tags/llama-cpp.md>), [llm](<https://devfeed.tech/tags/llm.md>), [local-ai](<https://devfeed.tech/tags/local-ai.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [superintelligence](<https://devfeed.tech/tags/superintelligence.md>), [user-experience](<https://devfeed.tech/tags/user-experience.md>)

### AI overview

Georgi Gerganov and the ggml team are joining Hugging Face to support the llama.cpp and ggml communities while retaining autonomy over technical direction and community leadership. The collaboration will provide long-term resources, improve integration between model definitions and llama.cpp, simplify packaging and user experience, and expand access to efficient local inference on devices.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.

## Introduction to ggml

DevFeed: [Introduction to ggml](<https://devfeed.tech/articles/introduction-to-ggml-7294.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/introduction-to-ggml>)

Author: Xuan-Son Nguyen; Georgi Gerganov; slaren

Published: 2024-08-13T00:00:00Z

Content type: tutorial

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [ggml](<https://devfeed.tech/topics/ggml.md>), [Programming](<https://devfeed.tech/topics/programming.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [Compression](<https://devfeed.tech/topics/compression.md>), [cpu](<https://devfeed.tech/topics/cpu.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [CUDA](<https://devfeed.tech/topics/cuda.md>), [Inference](<https://devfeed.tech/topics/inference.md>)

Tags: [community](<https://devfeed.tech/tags/community.md>), [compression](<https://devfeed.tech/tags/compression.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [cuda](<https://devfeed.tech/tags/cuda.md>), [ggml](<https://devfeed.tech/tags/ggml.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [guide](<https://devfeed.tech/tags/guide.md>), [llama-cpp](<https://devfeed.tech/tags/llama-cpp.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [programming](<https://devfeed.tech/tags/programming.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

An introductory developer tutorial on ggml, a low-level library for efficient tensor computation. It explains ggml's minimalism, compilation requirements, small binary size, hardware compatibility, quantized tensors, memory efficiency, limitations, and fundamental concepts, including how to compile it on Ubuntu.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.