huawei-csl/MACaQ
SOTA model-agnostic quantization for GGUF, local inference and beyond. Quantize and run text, image, video and audio models with llama.cpp, vLLM, Diffusers and PyTorch.
⚡ Executive Summary & Quick Facts
Authoritative SourceMACaQ is MACaQ is an open-source project written in C++: SOTA model-agnostic quantization for GGUF, local inference and beyond. Quantize and run text, image, video and audio models with llama.cpp, vLLM, Diffusers and PyTorch..
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of November 2026), huawei-csl/MACaQ has accumulated 187 GitHub stars and 8 forks. It is written in C++, licensed under Apache-2.0, and ranks #19,876 globally. It is actively maintained with the latest commit recorded on Nov 12, 2026.”
| Repository | huawei-csl/MACaQ ↗ |
|---|---|
| Primary Category | ascend |
| Language & Stack | C++ |
| Software License | Apache-2.0 |
| Community Traction | ★ 187 stars · ⑂ 8 forks · #19,876 globally |
| Maintenance | ● Active (Last commit: Nov 12, 2026) · 2 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+Yes, MACaQ is actively maintained. Continuous telemetry recorded the last code commit on Nov 12, 2026 (1 days ago). Supported by 187 stars and 8 community forks, this repository holds a calculated health index of 93/100, reflecting very active (commits within last 14 days) and healthy issue cadence.
Star History
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+10
STARS · LAST 30 DAYS
1
PER DAY
#1,581
MOST-STARRED C++
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +7 | +10 | +90 |
| Per day | 1 | 1 | 1 |
| Forks gained | +1 | +3 | +10 |
MACaQ gained 10 stars in the last 30 days, about 1 a day, and now has 187. It is about 1 year old and has averaged roughly 187 stars a year. It ranks #1,581 among C++ repositories and #19,876 across all languages on GitHubRepo.
Trending Record
1
DAYS ON TRENDING
#20127
BEST RANK
Nov 12, 2026
FIRST APPEARANCE
Active
STATUS TODAY
MACaQ has maintained a continuous presence across global trending indexes, peaking at #20127. Below is the 30-day activity profile:
💡 Overview
MACaQ is an open-source project written in C++: SOTA model-agnostic quantization for GGUF, local inference and beyond. Quantize and run text, image, video and audio models with llama.cpp, vLLM, Diffusers and PyTorch.
Engineered for speed, consistency, and developer ease, it solves common hurdles in ascend, audio, audio-generation. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in C++ for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ git clone https://github.com/huawei-csl/MACaQ.git
cd MACaQ⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
C++20 compliant compiler (GCC 11+, Clang 13+, MSVC)
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
MACaQ 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 MACaQ.
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
Install MACaQ using your package manager: `git clone https://github.com/huawei-csl/MACaQ.git`
Initialize your project workspace or configuration file for MACaQ.
Import MACaQ into your codebase or invoke it directly from your terminal.
Execute your test suite or run `MACaQ --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 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
huawei-csl/MACaQ is currently ranked #19,876 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #19,821 | suvamneog/jobradar | Python | ★ 188 | Compare ↗ |
| #19,821 | CIS-C0/RFSentinel | Kotlin | ★ 188 | Compare ↗ |
| #19,821 | RafaelNGP/psbox-cloud-gaming | C++ | ★ 188 | Compare ↗ |
| #19,821 | Gentleman-Programming/gentle-dot | TypeScript | ★ 188 | Compare ↗ |
| #19,821 | saulob/odin-sphere-leifthrasir-pc | C++ | ★ 188 | Compare ↗ |
| #19,876 | huawei-csl/MACaQ This Project | C++ | ★ 187 | |
| #19,876 | rikrd/geomerative | Java | ★ 187 | Compare ↗ |
| #19,876 | dicom/ruby-dicom | Ruby | ★ 187 | Compare ↗ |
| #19,876 | mit-carbon/Graphite | GLSL | ★ 187 | Compare ↗ |
| #19,876 | benwbrum/fromthepage | Ruby | ★ 187 | Compare ↗ |
| #19,876 | mozilla/mozregression | Python | ★ 187 | Compare ↗ |
Frequently Asked Questions
What does MACaQ do? +
SOTA model-agnostic quantization for GGUF, local inference and beyond. Quantize and run text, image, video and audio models with llama.cpp, vLLM, Diffusers and PyTorch.
Is MACaQ actively maintained in 2026? +
Yes, MACaQ is actively maintained. The latest code push was recorded on Nov 12, 2026 (1 days ago). It holds a calculated Maintenance Health Score of 93/100 (A+ rating) with 187 stars and 2 open issues.
What language is MACaQ written in? +
The primary language is C++. Topics include: ascend, audio, audio-generation, diffusers, gguf.
How many stars does MACaQ have? +
MACaQ has 187 stars and 8 forks on GitHub.
How does MACaQ rank among GitHub repositories? +
With 187 stars, huawei-csl/MACaQ is ranked #19,876 globally across all repositories tracked on GitHubRepo and #1,581 among C++ projects.
What license is MACaQ distributed under? +
The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.
