# Hugo vs Jekyll: source lines of code compared

The Hugo vs Jekyll comparison on OctoCounts shows side-by-side source line counts for gohugoio/hugo and jekyll/jekyll, counted with the same engine and analysis options on the dates shown in the methodology line: files, total lines, code lines, comment lines, blank lines, and per-language totals, pinned to the exact commits listed below.

As of 2026-08-26, gohugoio/hugo contains 253,710 total lines (181,215 code) across 1,104 files, while jekyll/jekyll contains 58,705 total lines (28,177 code) across 699 files as of 2026-09-03. gohugoio/hugo is about 6.4x the size of jekyll/jekyll by code lines. Code size is not code quality: a larger count only means more source material, not a better or worse project.

| Metric | [gohugoio/hugo](https://octocounts.com/github/gohugoio/hugo) | [jekyll/jekyll](https://octocounts.com/github/jekyll/jekyll) |
| --- | ---: | ---: |
| Files | 1,104 | 699 |
| Total lines | 253,710 | 58,705 |
| Code lines | 181,215 | 28,177 |
| Comment lines | 37,302 | 20,924 |
| Blank lines | 35,193 | 9,604 |
| Languages counted | 12 | 12 |

Top languages in gohugoio/hugo: Go (94.5% of code), JavaScript (2.0% of code), C (2.0% of code). Top languages in jekyll/jekyll: Ruby (60.0% of code), Gherkin (Cucumber) (16.2% of code), Sass (7.5% of code). JavaScript, YAML appear in both top language lists; Go, C, HTML appear only in gohugoio/hugo's top languages; Ruby, Gherkin (Cucumber), Sass appear only in jekyll/jekyll's top languages.

Methodology: both counts come from cached OctoCounts reports generated with tokei. gohugoio/hugo was counted at ref master (commit 166d3ee1ce94) on 2026-08-26; jekyll/jekyll was counted at ref master (commit 74d751339d3e) on 2026-09-03. See the [counting methodology](https://octocounts.com/docs/methodology) for ignored directories and analysis options.
## About this comparison

gohugoio/hugo counts the Hugo repository: the Go static site generator — its build pipeline, template and content handling, and embedded assets for the tool itself. jekyll/jekyll counts the Jekyll repository: the Ruby static site generator, its core, and its documentation and test suites. Both are generator source trees, not sites built with them, and both were counted on the dates in the methodology line above.

The per-language tables show the implementation-language contrast plainly: Hugo's counted code is Go, while Jekyll's is Ruby — two generators addressing the same task in different language ecosystems.

Both repositories carry documentation, fixtures, and tests alongside the generator core; for mature single-purpose tools, that supporting material forms a substantial share of the totals.

_Generator repository size says nothing about build speed, theme availability, or how large a generated site becomes; those depend on configuration, themes, and plugins, not on the tool's own line count._

Sources: [gohugoio/hugo repository](https://github.com/gohugoio/hugo) · [jekyll/jekyll repository](https://github.com/jekyll/jekyll). Statements verified 2026-09-16.

Evidence and next steps:

- [gohugoio/hugo SLOC report](https://octocounts.com/github/gohugoio/hugo)
- [jekyll/jekyll SLOC report](https://octocounts.com/github/jekyll/jekyll)
- [Compare gohugoio/hugo and jekyll/jekyll interactively](https://octocounts.com/compare?left=https%3A%2F%2Fgithub.com%2Fgohugoio%2Fhugo&right=https%3A%2F%2Fgithub.com%2Fjekyll%2Fjekyll)

Note: code size is not code quality. OctoCounts only reports reproducible line counts and makes no claim that either project is better.

## Compare FAQ

### Which has more lines of code, gohugoio/hugo or jekyll/jekyll?

gohugoio/hugo has more code: 181,215 code lines versus 28,177 for jekyll/jekyll, about 6.4x as much, based on cached OctoCounts reports as of 2026-09-03.

### Does more source lines of code mean more complexity?

Not necessarily. SLOC measures size, not complexity, quality, or maintainability. A larger codebase can mean more features, more generated or vendored code, more verbose language idioms, or more tests — none of which imply the code is harder to work with. Use SLOC to gauge the scale of what you'd be reading or maintaining, not as a quality signal for gohugoio/hugo, jekyll/jekyll, or any repository.

### How is this comparison calculated?

Methodology: both counts come from cached OctoCounts reports generated with tokei. gohugoio/hugo was counted at ref master (commit 166d3ee1ce94) on 2026-08-26; jekyll/jekyll was counted at ref master (commit 74d751339d3e) on 2026-09-03. See the counting methodology for ignored directories and analysis options.

### Can I compare a different branch, tag, or commit?

Yes. This page shows the default branch for each repository. Use the interactive comparison tool to pick any public GitHub repository, branch, tag, or commit SHA for both sides and get a fresh side-by-side report.

## Related OctoCounts pages

- [Interactive repository comparison](https://octocounts.com/compare)
- [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)
- [Original research: how filtering changes SLOC counts](https://octocounts.com/research)
- [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)
- [OctoCounts API docs](https://octocounts.com/docs/api)