# tensorflow/tensorflow SLOC report

> As of 2026-09-16 (commit 69161e265503), tensorflow/tensorflow contains 6,792,427 total lines: 5,095,080 code, 951,341 comments, 746,006 blank, across 24,148 files in 40 languages (top: C++ 56.0%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

tensorflow/tensorflow has 5,095,080 source lines of code out of 6,792,427 total lines across 24,148 files, counted from the 69161e265503173695b265121e12250c45ff9a46 ref at commit 69161e265503 by the OctoCounts tokei engine on 2026-09-16. 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 tensorflow/tensorflow to commit 69161e265503, 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 very large codebase by counted code lines. Code represents 75.0% of all lines, comments represent 14.0%, and the repository averages 211 code lines per file. C++ accounts for 56.0% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| C++ | 10,454 | 3,629,352 | 2,854,966 | 385,363 | 389,023 |
| Python | 2,985 | 1,167,890 | 932,157 | 96,196 | 139,537 |
| C Header | 6,303 | 908,212 | 536,208 | 246,190 | 125,814 |
| Bazel | 1,601 | 385,680 | 333,537 | 28,351 | 23,792 |
| HTML | 238 | 340,053 | 320,111 | 3,078 | 16,864 |
| Go | 41 | 67,441 | 31,727 | 31,906 | 3,808 |
| Protocol Buffers | 351 | 37,567 | 15,515 | 16,315 | 5,737 |
| Pan | 76 | 15,182 | 12,640 | 1,401 | 1,141 |
| Shell | 229 | 17,596 | 9,583 | 5,808 | 2,205 |
| Java | 109 | 18,038 | 9,294 | 6,826 | 1,918 |
| Objective-C++ | 60 | 9,852 | 7,652 | 1,035 | 1,165 |
| Templ | 106 | 7,006 | 7,006 | 0 | 0 |

Top language (C++ 56.0%). Generated at 2026-09-16T20:54:35.133984963+00:00. Canonical report: https://octocounts.com/github/tensorflow/tensorflow

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/tensorflow/tensorflow/commit/69161e265503173695b265121e12250c45ff9a46?analysis=%7B%22ignoredDirs%22%3A%5B%5D%2C%22ignoredLanguages%22%3A%5B%5D%2C%22profile%22%3A%22default%22%2C%22includeDocs%22%3Afalse%2C%22includeTests%22%3Afalse%2C%22includeGenerated%22%3Afalse%7D).

## Report FAQ

### How many lines of code does tensorflow/tensorflow have?

tensorflow/tensorflow has 6,792,427 total lines, including 5,095,080 code lines, 951,341 comment lines, and 746,006 blank lines.

### How was the tensorflow/tensorflow line count measured?

OctoCounts resolved the public GitHub repository to commit 69161e265503, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for tensorflow/tensorflow?

This OctoCounts report was generated from 69161e265503173695b265121e12250c45ff9a46 at commit 69161e265503 on 2026-09-16T20:54:35.133984963+00:00.

## Similar repository reports

- [facebook/hhvm](https://octocounts.com/github/facebook/hhvm) — C++, 4,641,684 code lines
- [mongodb/mongo](https://octocounts.com/github/mongodb/mongo) — C++, 5,888,453 code lines
- [godotengine/godot](https://octocounts.com/github/godotengine/godot) — C++, 4,110,443 code lines
- [RosettaCommons/rosetta](https://octocounts.com/github/RosettaCommons/rosetta) — C++, 4,032,379 code lines
- [LibreOffice/core](https://octocounts.com/github/LibreOffice/core) — C++, 6,334,759 code lines
- [microsoft/onnxruntime](https://octocounts.com/github/microsoft/onnxruntime) — C++, 2,408,506 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)
- [Electron vs Tauri](https://octocounts.com/compare/electron-vs-tauri)
- [Godot vs Bevy](https://octocounts.com/compare/godot-vs-bevy)
- [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)