# XiaomiMiMo/verl SLOC report

> XiaomiMiMo/verl: 130,616 code lines at commit a2ad9f6160b0, counted with tokei-12.1 on 2026-09-26. Saved result 53d7e8b1880c1ecde20552dec04fd7d4f29a8d824accc3f07c2f7bd5bf51e13c.

XiaomiMiMo/verl has 130,616 source lines of code out of 173,541 total lines across 773 files, counted from the mimo-oss ref at commit a2ad9f6160b0 by the OctoCounts tokei engine on 2026-09-26. 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 XiaomiMiMo/verl to commit a2ad9f6160b0, 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 75.3% of all lines, comments represent 11.5%, and the repository averages 169 code lines per file. Python accounts for 79.7% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| Python | 475 | 134,892 | 104,143 | 13,012 | 17,737 |
| Shell | 160 | 22,094 | 17,718 | 1,843 | 2,533 |
| YAML | 78 | 9,640 | 6,895 | 1,477 | 1,268 |
| JavaScript | 2 | 1,228 | 1,199 | 19 | 10 |
| Jupyter Notebooks | 2 | 700 | 491 | 113 | 96 |
| TOML | 2 | 161 | 82 | 61 | 18 |
| HTML | 1 | 45 | 45 | 0 | 0 |
| JSON | 2 | 43 | 43 | 0 | 0 |
| Markdown | 47 | 4,681 | 0 | 3,412 | 1,269 |
| Plain Text | 4 | 57 | 0 | 57 | 0 |

Top language (Python 79.7%). Generated at 2026-09-26T08:17:43.072260501Z. Canonical report: https://octocounts.com/github/XiaomiMiMo/verl/commit/a2ad9f6160b03ff2d47e59832bfb6b289f37c917?reportId=53d7e8b1880c1ecde20552dec04fd7d4f29a8d824accc3f07c2f7bd5bf51e13c&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/XiaomiMiMo/verl/commit/a2ad9f6160b03ff2d47e59832bfb6b289f37c917?reportId=53d7e8b1880c1ecde20552dec04fd7d4f29a8d824accc3f07c2f7bd5bf51e13c&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 XiaomiMiMo/verl have?

XiaomiMiMo/verl has 173,541 total lines, including 130,616 code lines, 19,994 comment lines, and 22,931 blank lines.

### How was the XiaomiMiMo/verl line count measured?

OctoCounts resolved the public GitHub repository to commit a2ad9f6160b0, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for XiaomiMiMo/verl?

This OctoCounts report was generated from mimo-oss at commit a2ad9f6160b0 on 2026-09-26T08:17:43.072260501Z.

## Similar repository reports

- [factorysemantics/factorysemantics-mes](https://octocounts.com/github/factorysemantics/factorysemantics-mes) — Python, 128,935 code lines
- [CellProfiler/CellProfiler](https://octocounts.com/github/CellProfiler/CellProfiler) — Python, 133,069 code lines
- [AndrewAltimit/exploits](https://octocounts.com/github/AndrewAltimit/exploits) — Python, 133,329 code lines
- [ansible/ansible](https://octocounts.com/github/ansible/ansible) — Python, 127,869 code lines
- [TheAlgorithms/Python](https://octocounts.com/github/TheAlgorithms/Python) — Python, 127,292 code lines
- [InnerAura/hyperweave](https://octocounts.com/github/InnerAura/hyperweave) — Python, 135,436 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)
