model-optimizer
NVIDIA Model Optimizer is an open-source library that compresses large AI models, through techniques like quantization and pruning, so they run several times faster and cheaper at inference time without losing much accuracy.
View nvidia/model-optimizer on GitHub- GitHub stars
- 5,600
- Forks
- —
- Language
- Python
Project details
- Repository
- nvidia/model-optimizer
- Licence
- Apache-2.0
- Primary language
- Python
- Catalog status
- Available
- Catalog check
- 2026-11-13
Repository description
A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like TensorRT-LLM, TensorRT, vLLM, etc. to optimize inference speed.
Explore by topic
More tools in Models & training
- opencode
anomalyco · MIT
OpenCode is a free, open-source AI coding agent you run from your terminal, an alternative to tools like Claude Code or Cursor that works with any LLM provider.
- transformers
huggingface · Apache-2.0
The open-source library that provides ready-to-use implementations of virtually every major AI model for text, vision, audio, and multimodal use, letting developers run…
- comfyui
comfy-org · GPL-3.0
ComfyUI is a free, node-based visual interface for running diffusion models like Stable Diffusion locally, so you can build AI image and video generation workflows by…
- pi
earendil-works · MIT
An open-source toolkit for building AI agents: one unified API across OpenAI, Anthropic and Google models, plus a ready-made interactive coding agent CLI.