# NVIDIA/Model-Optimizer SLOC report

> NVIDIA/Model-Optimizer: 221,867 code lines at commit 92a3cd50a6b0, counted with tokei-14.0.0 on 2026-10-21. Saved result e103415bb686ad44491258b96dfe33f0fab2e10f1987a5366c676db99d00c992.

NVIDIA/Model-Optimizer has 221,867 source lines of code out of 320,211 total lines across 1,650 files, counted from the main ref at commit 92a3cd50a6b0 by the OctoCounts tokei engine on 2026-10-21. The report is cached by commit, tokei version, and analysis options, so recounting the same revision returns exactly these numbers.

OctoCounts produced this report by resolving NVIDIA/Model-Optimizer to commit 92a3cd50a6b0, downloading the repository source archive, and counting every source file with tokei, the open-source line counter written in Rust. The table below breaks the count down by programming language into files, total lines, code lines, comment lines, and blank lines, so the figures can be compared across languages and projects. Results are cached by commit, tokei version, and analysis options, so counting the same revision again reproduces exactly these numbers.

## Repository size insights

This is a large codebase by counted code lines. Code represents 69.3% of all lines, comments represent 17.3%, and the repository averages 134 code lines per file. Python accounts for 89.9% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| Python | 905 | 259,867 | 199,386 | 27,973 | 32,508 |
| YAML | 413 | 22,156 | 12,942 | 7,540 | 1,674 |
| Shell | 60 | 6,648 | 4,033 | 1,778 | 837 |
| CUDA | 10 | 2,073 | 1,357 | 420 | 296 |
| Jupyter Notebooks | 16 | 1,816 | 1,112 | 423 | 281 |
| ReStructuredText | 1 | 1,147 | 888 | 0 | 259 |
| Jinja2 | 6 | 838 | 703 | 105 | 30 |
| C++ | 8 | 790 | 509 | 171 | 110 |
| TOML | 4 | 498 | 384 | 63 | 51 |
| C Header | 5 | 521 | 276 | 153 | 92 |
| JSON | 5 | 201 | 201 | 0 | 0 |
| Dockerfile | 2 | 107 | 55 | 30 | 22 |
| CMake | 1 | 41 | 17 | 16 | 8 |
| Autoconf | 1 | 9 | 4 | 5 | 0 |
| Markdown | 185 | 23,317 | 0 | 16,459 | 6,858 |
| Plain Text | 28 | 182 | 0 | 177 | 5 |

Top language (Python 89.9%). Generated at 2026-10-21T02:53:46.158364682Z. Canonical report: https://octocounts.com/github/NVIDIA/Model-Optimizer/commit/92a3cd50a6b0f051fbfac6fa56805b97f2dde351?reportId=e103415bb686ad44491258b96dfe33f0fab2e10f1987a5366c676db99d00c992&analysis=%7B%22profile%22%3A%22default%22%2C%22ignoredDirs%22%3A%5B%5D%2C%22includeDocs%22%3Afalse%2C%22includeTests%22%3Afalse%2C%22ignoredLanguages%22%3A%5B%5D%2C%22includeGenerated%22%3Afalse%7D

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/NVIDIA/Model-Optimizer/commit/92a3cd50a6b0f051fbfac6fa56805b97f2dde351?reportId=e103415bb686ad44491258b96dfe33f0fab2e10f1987a5366c676db99d00c992&analysis=%7B%22profile%22%3A%22default%22%2C%22ignoredDirs%22%3A%5B%5D%2C%22includeDocs%22%3Afalse%2C%22includeTests%22%3Afalse%2C%22ignoredLanguages%22%3A%5B%5D%2C%22includeGenerated%22%3Afalse%7D).

## Report FAQ

### How many lines of code does NVIDIA/Model-Optimizer have?

NVIDIA/Model-Optimizer has 320,211 total lines, including 221,867 code lines, 55,313 comment lines, and 43,031 blank lines.

### How was the NVIDIA/Model-Optimizer line count measured?

OctoCounts resolved the public GitHub repository to commit 92a3cd50a6b0, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for NVIDIA/Model-Optimizer?

This OctoCounts report was generated from main at commit 92a3cd50a6b0 on 2026-10-21T02:53:46.158364682Z.

## Similar repository reports

- [sqlalchemy/sqlalchemy](https://octocounts.com/github/sqlalchemy/sqlalchemy) — Python, 222,905 code lines
- [dograh-hq/dograh](https://octocounts.com/github/dograh-hq/dograh) — Python, 224,133 code lines
- [strands-agents/harness-sdk](https://octocounts.com/github/strands-agents/harness-sdk) — Python, 219,536 code lines
- [open-jarvis/OpenJarvis](https://octocounts.com/github/open-jarvis/OpenJarvis) — Python, 226,415 code lines
- [vitali87/code-graph-rag](https://octocounts.com/github/vitali87/code-graph-rag) — Python, 215,082 code lines
- [K-Dense-AI/scientific-agent-skills](https://octocounts.com/github/K-Dense-AI/scientific-agent-skills) — Python, 230,344 code lines

## Related OctoCounts pages

- [Recently analyzed repositories](https://octocounts.com/recent)
- [Popular SLOC reports](https://octocounts.com/popular)
- [Trending GitHub repositories](https://octocounts.com/trending)
- [Hall of Monoliths](https://octocounts.com/hall-of-monoliths)
- [TensorFlow vs PyTorch](https://octocounts.com/compare/tensorflow-vs-pytorch)
- [Django vs Ruby on Rails](https://octocounts.com/compare/django-vs-rails)
- [Laravel vs Django](https://octocounts.com/compare/laravel-vs-django)
- [GitHub SLOC counter guide](https://octocounts.com/docs/github-sloc-counter)
- [Counting methodology](https://octocounts.com/docs/methodology)
- [SLOC and code metrics glossary](https://octocounts.com/docs/glossary)
- [Original research: how filtering changes SLOC counts](https://octocounts.com/research)
- [OctoCounts API docs](https://octocounts.com/docs/api)