Quarto vs R Markdown in 2026: Which Should You Use?

A Quarto vs R Markdown comparison matters in 2026 because the choice affects your entire reproducible research workflow. R Markdown has been the backbone of reproducible research in R for over a decade. Quarto, released in 2022, is now positioned as its official successor. If you are still using R Markdown, or if you are starting fresh, understanding the Quarto vs R Markdown trade-offs matters for your workflow.

This guide compares Quarto and R Markdown as they stand in 2026, with practical guidance on which to choose.

The short answer

Use Quarto for new projects. It is actively developed, supports more languages and output formats, and has a cleaner architecture. R Markdown is not going away—millions of documents exist and will continue to work—but new features come to Quarto first.

That said, R Markdown still makes sense in specific situations. Let us dig into the details.

What Quarto changes

Unified configuration

The most immediate difference is how you configure documents. In R Markdown, you often needed a separate setup chunk to set chunk options:

# R Markdown: configuration lives in a setup chunk
knitr::opts_chunk$set(echo = TRUE, fig.width = 8)

In Quarto, everything goes in the YAML header, which the IDE can autocomplete and the rendering engine can validate before execution. Moving chunk options into the document preamble makes your .qmd file self-documenting: a new reader or collaborator sees the output format, figure dimensions, and code visibility settings at the top, without scrolling through code chunks. This centralisation also means that tools like RStudio and VS Code can offer schema-aware autocompletion for every option. Here is the Quarto equivalent:

---
title: "My Document"
format:
  html:
    echo: true
    fig-width: 8
---

This seems like a small change, but it makes documents cleaner and keeps configuration in one place. You also get editor support—IDE autocompletion for YAML options that does not exist in R Markdown.

More output formats

Quarto ships with more built-in output formats out of the box:

• HTML, PDF, Word (same as R Markdown)
• Revealjs presentations, native, no separate package needed
• Jupyter notebooks, Quarto renders .ipynb files directly
• Websites and blogs, built-in project types
• Books, full documentation site generation

For R Markdown, many of these required additional packages (bookdown, blogdown, revealjs). Quarto bakes them in.

Multi-Language support

R Markdown is R-centric. Quarto started with R but added native support for Python, Julia, and Observable JavaScript:

---
title: "Analysis"
format: html
---

This same document can run R code, Python code, and JavaScript, each in its own engine—without wrapper packages. If your team uses multiple languages, Quarto eliminates the need for separate workflows.

Better cross-References

Quarto handles figure, table, and equation cross-references more consistently. You reference a figure with @fig-density:

#| label: fig-density
#| fig-cap: "Density Plot"
plot(density(x))

Then in prose you write See @fig-density for the distribution. and Quarto resolves the number automatically.

The #| syntax (inspired by Jupyter) replaces R Markdown’s chunk options with a cleaner format that works across languages.

Where R markdown still wins

Package dependencies

R Markdown lives in the rmarkdown package, which has been stable for years. Quarto is a separate installation: a standalone CLI tool that runs independently of R. Some environments (like certain RStudio Server configurations) make installing Quarto tricky.

If you are in a restricted environment where you cannot install external tools, R Markdown remains the practical choice.

Legacy documents

If you have an existing R Markdown project with dozens or hundreds of documents, migrating to Quarto is not trivial. The syntax differences are not huge, but cumulative migration takes time.

For maintainers of large R Markdown codebases, the question is whether the benefits justify the migration cost. In 2026, many teams are making that transition, but it is not instantaneous.

Specific package features

Some R Markdown extensions do not yet have Quarto equivalents. The rgl package for 3D graphics renders more reliably in R Markdown. Certain Shiny-specific features work better in R Markdown documents.

Check your specific dependencies before switching.

Feature comparison

Feature	R Markdown	Quarto
Active development	Maintenance mode	Active
Output formats	Requires packages	Built-in
Multi-language	R only	R, Python, Julia, JS
Configuration location	YAML + setup chunks	YAML only
Cross-references	Via bookdown	Native
Website generation	Via blogdown	Built-in
Jupyter support	No	Yes
VS Code support	Limited	Full

Migration path

If you decide to migrate, the good news is that most R Markdown documents work with minimal changes:

1. Install Quarto, Download from quarto.org
2. Render with Quarto, quarto render document.Rmd often works directly
3. Update chunk options, Convert {#r chunk-label, option=value} to #| label: chunk-label, option: value
4. Move YAML options, Pull knitr::opts_chunk$set() settings into the YAML header

RStudio and Posit Connect have built-in migration guides that handle many of these automatically.

Migrating from R Markdown to Quarto is incremental. Most .Rmd files render unchanged with Quarto after renaming to .qmd, the YAML front matter and code chunk syntax are compatible. The main migration task is updating chunk options from {r, echo=FALSE} syntax to the #| echo: false style that Quarto prefers. The knitr.chunk.defaults option controls global defaults in both systems. For large collections of documents, migrate one document at a time, verifying output before proceeding to the next.

What you should do

1. Use Quarto for all new work, It is the future, and the investment pays off.
2. Migrate when convenient, Do not rush, but plan to move existing projects over time.
3. Check package compatibility, Before migrating, verify your critical packages work with Quarto.
4. Learn the YAML configuration, It is cleaner than setup chunks once you get used to it.
5. Explore built-in formats, Websites, books, and presentations are easier in Quarto.

Quarto is not just R Markdown 2.0; it is a different philosophy that unifies computational documents across languages. The transition is worth it for most users in 2026.

The ecosystem and tooling

Quarto integrates with multiple editors: RStudio has first-class Quarto support with a visual editor and live preview. VS Code uses the Quarto extension, which provides syntax highlighting, chunk execution, and a preview pane. Positron (Posit’s new IDE) is built around Quarto from the start. R Markdown, by contrast, is tightly coupled to RStudio and the knitr infrastructure, it works in other editors but without the same integration.

The Quarto documentation and community resources have grown substantially since its 2022 release. Extension repositories on GitHub provide custom formats, journal templates (JASA, Elsevier, ACS), and HTML/PDF themes. The extension system, which uses Lua filters and SCSS, is more accessible than R Markdown’s infrastructure for users who want to customize output.

Version compatibility: Quarto is versioned independently from R packages. A Quarto project pins the version in _quarto.yml. R Markdown projects are pinned through the rmarkdown package version in renv.lock. For long-term reproducibility, both systems require explicit version management, Quarto’s separation from R packaging makes it slightly simpler to pin the computational document rendering engine independently of the R package ecosystem.

When to use each

Choose Quarto when:

1. Starting a new project, Any new reproducible document or website should use Quarto.
2. Building websites or books, The built-in project types are cleaner than blogdown/bookdown.
3. Using multiple languages, Python and R in the same workflow is smooth.
4. Wanting active development, New features and bug fixes go to Quarto first.
5. Creating presentations, Revealjs is included without extra setup.

Choose R markdown when:

1. Maintaining existing projects, If it works, no need to migrate just for the sake of it.
2. Restricted environments, Cannot install Quarto CLI.
3. Using rgl or specific packages, Check compatibility first.
4. Team resistance to change, Migration has a learning curve.

See also

• quarto-guide, Getting started with Quarto
• r-markdown-guide, R Markdown reference
• r-markdown-tutorial, R Markdown basics