← Back to home
Comparison · Analytics

cmdstanr vs workflows

A side-by-side editorial comparison of cmdstanr and workflows — release velocity, themes, recent moves, and the top alternatives to consider.

cmdstanr vs workflows: at a glance

Featurecmdstanrworkflows
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesbayesian inference, stan, approximate inference, windows toolchaintidymodels, pipelines, postprocessing, sparse-data
Last editorial update2h ago49m ago
WebsiteVisit →Visit →

What is cmdstanr?

cmdstanr keeps adding fast approximations beside full HMC, and fighting Windows toolchains.

cmdstanr is the lightweight R interface to CmdStan, shelling out to the Stan binary rather than embedding it. The visible releases pair inference-method expansion, with laplace and pathfinder arriving in 0.7.0, against a continuous effort to make installation work on Windows. The most recent releases are dominated by CmdStan version compatibility and numerical fixes in the loo path.

Read the full cmdstanr trajectory →

What is workflows?

The tidymodels pipeline grew a third stage, and it happens after the model runs.

workflows bundles a preprocessor and a model into one object that tidymodels can fit, tune and extract from. Version 1.3.0 added a post stage backed by the tailor package, wired through every generic a workflow supports — augment, tidy, tunable, tune_args, required_pkgs and parameter extraction. Version 1.2.0 added sparse data support so fit() and predict() accept dgCMatrix and sparse tibbles. Earlier releases in view are boundary tightening: erroring on unknown model modes, on trained recipes, and on silently ignored formula offsets.

Read the full workflows trajectory →

cmdstanr vs workflows: editorial side-by-side

C
cmdstanr
ANALYTICS
0.0

cmdstanr keeps adding fast approximations beside full HMC, and fighting Windows toolchains.

◆ Current state

cmdstanr is the lightweight R interface to CmdStan, shelling out to the Stan binary rather than embedding it. The visible releases pair inference-method expansion, with laplace and pathfinder arriving in 0.7.0, against a continuous effort to make installation work on Windows. The most recent releases are dominated by CmdStan version compatibility and numerical fixes in the loo path.

◆ Where it's heading

The package tracks CmdStan closely, and its own work concentrates in two places. One is broadening the method surface so approximate inference sits beside sampling on the same object, extended in 0.8.0 by letting a completed fit supply initial values for the next run. The other is cutting installation friction, which reaches its conclusion in 0.9.0 with RTools45 supported and no additional toolchain setup needed on Windows. Dependency trimming, such as dropping RcppEigen for direct Eigen interop, runs alongside both.

◆ Prediction

The cadence is a CmdStan release followed by a compatibility release here, so expect the next to track a newer CmdStan and continue the effective-sample-size numerical work in the loo method.

W
workflows
ANALYTICS
0.0

The tidymodels pipeline grew a third stage, and it happens after the model runs.

◆ Current state

workflows bundles a preprocessor and a model into one object that tidymodels can fit, tune and extract from. Version 1.3.0 added a post stage backed by the tailor package, wired through every generic a workflow supports — augment, tidy, tunable, tune_args, required_pkgs and parameter extraction. Version 1.2.0 added sparse data support so fit() and predict() accept dgCMatrix and sparse tibbles. Earlier releases in view are boundary tightening: erroring on unknown model modes, on trained recipes, and on silently ignored formula offsets.

◆ Where it's heading

The object is filling out into a complete pipeline description rather than a preprocessing-plus-model pair. Postprocessing is the structural addition — calibration and threshold selection were previously done by hand after prediction, outside anything tidymodels could tune or record — and the fact that it arrived integrated with tunable() and tune_args() rather than as a standalone step is the point. The rest of the arc is the steady tidymodels habit of converting silent guesses into errors.

◆ Prediction

Expect tailor postprocessors to spread through tune and workflowsets next, since the parameter and tuning generics were wired up first, and expect sparse support to extend to more engines after lightgbm.

Alternatives to cmdstanr and workflows

Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either cmdstanr or workflows.

See all cmdstanr alternatives → · See all workflows alternatives →

Recent activity from cmdstanr and workflows

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 4mo agocmdstanrRTools45 support; Windows needs no extra toolchain setup
  2. 4mo agocmdstanrBugfix release: SUNDIALS linking, Windows paths, RTools
  3. 4mo agocmdstanrCmdStanFit objects usable as initial values; RcppEigen dropped
  4. 11mo agoworkflowsWorkflows gain a postprocessing stage via tailor
  5. 1y agoworkflowsSparse matrices work through fit() and predict()
  6. 2y agoworkflowsaugment() aligns with parsnip; censored regression supported
  7. 2y agocmdstanrBugfix release with dedicated hpp generation step
  8. 2y agocmdstanrLaplace and Pathfinder inference methods added
  9. 2y agocmdstanrjacobian argument enabled for optimization; assorted fixes
  10. 3y agoworkflowsRegister tuning generics unconditionally
  11. 3y agoworkflowsMissing parsnip extensions now error early; unsupervised specs supported
  12. 3y agoworkflowsMode guessing removed; silent offset handling now errors

Frequently asked questions

What is the difference between cmdstanr and workflows?

They serve adjacent needs but don't currently overlap on shipped themes. cmdstanr and workflows are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is cmdstanr better than workflows?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cmdstanr and workflows are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to cmdstanr?

Top cmdstanr alternatives in Analytics are ranked by recent ship velocity. Browse the "cmdstanr alternatives" section above for the current picks, or visit /alternatives/cmdstanr for the full list with editorial commentary on each.

What are the best alternatives to workflows?

Top workflows alternatives in Analytics are ranked by recent ship velocity. Browse the "workflows alternatives" section above for the current picks, or visit /alternatives/workflows-r for the full list with editorial commentary on each.