GGML
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Overview
HEALTH SCORE
Healthy
74out of 100
Solid maintainer coverage and development cadence. Security posture keeps the score from reaching Excellent.
LIFECYCLE
Active
Consistent commits, responsive maintainers, regular releases, and healthy issue triage.
Health breakdown
Healthy(74/100)
Maintainer availability, known risks and supply chain posture, and whether the project is actively developed or appropriately stable.
Maintainer responsiveness
Median response time is 1 day.
Bus factor
35 active maintainers currently have merge rights.
Organization Diversity
Contributors span 557 organizations.
Project Achievements
Leaderboards
About
GGML is a tensor library for machine learning that enables efficient neural network inference on CPU. It provides low-level primitives for implementing deep learning models with a focus on performance and memory efficiency, particularly for running large language models on consumer hardware.
First commit
Software value
$11M
Tags
automatic-differentiation
large-language-models
machine-learning
tensor-algebra
License(s)
MIT
Links
Data sources
Git
GitHub