workflowstacks
ai-agent

GPTQModel: Faster AI

Compress AI models with GPTQModel, a toolkit.
1,225 stars199 forksPythonGuide quality 8/10Updated 8/11/2026100% free · open source
What it does

GPTQModel compresses large language models to reduce their size and improve deployment efficiency on various hardware platforms, including Nvidia, AMD, Intel, and Apple CPUs and GPUs.

When to use it
  • •When deploying AI models on edge devices with limited storage or computational resources
  • •When reducing the latency and cost of inference in cloud-based AI applications
  • •When optimizing AI model size and speed for real-time customer interactions, such as chatbots or voice assistants
Ready-to-paste prompt
python -m gptqmodel.quantize --model gpt2 --config quantization_config.json --hardware accelerator=nvidia
Heads up: Ensure you have the correct version of the `torch` and `transformers` libraries installed, as GPTQModel relies on these dependencies for model quantization and hardware acceleration
Saves to your device
Use with Claude
New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

✅ Light setup

Installs with a command or two; your AI agent can do it for you.

Try it instantly — no install
Claude Code
mkdir -p ~/.claude/skills/gptqmodel && curl -fsSL https://workflowstacks.com/api/skills/gptqmodel/claude-skill -o ~/.claude/skills/gptqmodel/SKILL.md
Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)
claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

How GPTQModel: Faster AI works
Codeflow
Free to inspect

GPTQModel: Faster AI is a very large Python project (~133k lines across 474 code files, plus 490 test files). Setup is light: installs like a normal app. Reading the code is optional. Last commit this month, Other license, has a test suite.

Size
Very large codebase
~133k lines · 474 code files · days to read — use, don't read
Setup
One-command install
Installs like a normal app. Reading the code is optional.
Runs on
Python
No API keys detected
Python 83%Cuda 11%C++ 5%
Where to start reading
  1. 1
    README.md
    Start here — what it does and how to install it
  2. 2
    AGENTS.md
    The instructions the AI actually follows
  3. 3
    pyproject.toml
    Dependencies and the commands it exposes
  4. 4
    gptqmodel/__init__.py
    Inside gptqmodel/ — the main logic begins here
What's in each folder
gptqmodel/Core code — the actual logic372 files
docs/Documentation11 files
gptqmodel_ext/Folder176 files
scripts/Helper scripts34 files
format/Folder2 files
licenses/Folder2 files
optimize/Folder2 files
hw/Folder1 files
READMEHas testsDocumentedCI checksOther licenseUpdated this month
Quick Actions
Details
Creator
ModelCloud
Language
Python
Category
ai-agent
Published
6/17/2024

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