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NVIDIA/Model-Optimizer

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.

Python Apache-2.0 main Stack scanned README.md
Stars
3,232
Forks
500
Watchers
31
Issues
317
Commits
1,050
Awesome lists
1

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Latest capture 2026-07-15 03:16

Star growth, last 7 days
0 0.0%
Commit velocity, last 7 days
0 0.0%
Stars since baseline
+473
Snapshot coverage
5

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5 captures since 2026-05-25

Stars from baseline +473

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Detected stack

Frameworks, package managers, ecosystems, and dependency manifests found during catalog scans.

Scanned 2026-07-15 03:16

Stack signals
1
Package managers
3
Manifest files
31
Dependencies
194

Frameworks and tools

  • pytest test framework · high confidence
CMake pip uv c-cpp python

Dependency files

31 manifests
  • pyproject.toml python ecosystem, 69 dependencies
  • uv.lock python ecosystem, 0 dependencies
  • examples/cnn_qat/requirements.txt python ecosystem, 1 dependency
  • examples/diffusers/requirements.txt python ecosystem, 2 dependencies
  • examples/gpt-oss/requirements.txt python ecosystem, 4 dependencies
  • examples/hf_ptq/requirements.txt python ecosystem, 5 dependencies
  • examples/llm_distill/requirements.txt python ecosystem, 3 dependencies
  • examples/llm_eval/requirements.txt python ecosystem, 5 dependencies
  • 23 more files

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AI development signals

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141 paths

AI agent config detected

141 config paths 103 files 38 directories
Agent instructions Agent workspace 116 Claude Code 23 CodeRabbit

Key config paths

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Showing the first 24 paths. 117 more detected.

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Metadata

Language
Python
License
Apache-2.0
Default branch
main
Created
2024-04-23
First commit
2024-05-08
Last pushed
2026-07-15
GitHub updated
2026-07-15
Last synced
2026-07-15 03:16
Stack detected
2026-07-15 03:16
Archived
no
GitHub Website

https://nvidia.github.io/Model-Optimizer/

README

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