# Blaizzy/mlx-audio SLOC report

> As of 2026-09-16 (commit aef6ebc20ddc), Blaizzy/mlx-audio contains 191,810 total lines: 154,095 code, 9,954 comments, 27,761 blank, across 800 files in 12 languages (top: Python 97.1%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

Blaizzy/mlx-audio has 154,095 source lines of code out of 191,810 total lines across 800 files, counted from the aef6ebc20ddc775ee62455f383bba141338b7c1c ref at commit aef6ebc20ddc 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 Blaizzy/mlx-audio to commit aef6ebc20ddc, 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 80.3% of all lines, comments represent 5.2%, and the repository averages 193 code lines per file. Python accounts for 97.1% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| Python | 703 | 182,757 | 149,622 | 7,167 | 25,968 |
| TSX | 16 | 3,704 | 3,213 | 129 | 362 |
| JSON | 7 | 626 | 623 | 0 | 3 |
| TypeScript | 4 | 334 | 259 | 30 | 45 |
| YAML | 1 | 128 | 124 | 0 | 4 |
| CSS | 1 | 140 | 118 | 5 | 17 |
| TOML | 1 | 147 | 109 | 13 | 25 |
| Autoconf | 1 | 14 | 12 | 1 | 1 |
| JavaScript | 2 | 14 | 10 | 2 | 2 |
| INI | 1 | 5 | 5 | 0 | 0 |
| Markdown | 59 | 3,907 | 0 | 2,573 | 1,334 |
| Plain Text | 4 | 34 | 0 | 34 | 0 |

Top language (Python 97.1%). Generated at 2026-09-16T19:07:10.758199719+00:00. Canonical report: https://octocounts.com/github/Blaizzy/mlx-audio

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/Blaizzy/mlx-audio/commit/aef6ebc20ddc775ee62455f383bba141338b7c1c?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 Blaizzy/mlx-audio have?

Blaizzy/mlx-audio has 191,810 total lines, including 154,095 code lines, 9,954 comment lines, and 27,761 blank lines.

### How was the Blaizzy/mlx-audio line count measured?

OctoCounts resolved the public GitHub repository to commit aef6ebc20ddc, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for Blaizzy/mlx-audio?

This OctoCounts report was generated from aef6ebc20ddc775ee62455f383bba141338b7c1c at commit aef6ebc20ddc on 2026-09-16T19:07:10.758199719+00:00.

## Similar repository reports

- [livekit/agents](https://octocounts.com/github/livekit/agents) — Python, 153,977 code lines
- [langchain-ai/open-swe](https://octocounts.com/github/langchain-ai/open-swe) — Python, 154,660 code lines
- [Osmantic/ODS](https://octocounts.com/github/Osmantic/ODS) — Python, 152,023 code lines
- [huggingface/text-generation-inference](https://octocounts.com/github/huggingface/text-generation-inference) — Python, 150,835 code lines
- [gradio-app/gradio](https://octocounts.com/github/gradio-app/gradio) — Python, 149,587 code lines
- [meta-pytorch/torchrec](https://octocounts.com/github/meta-pytorch/torchrec) — Python, 158,832 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)
