greta

Free#37 of 106 in Statistical Analysis Software

greta: A flexible R-native choice for Bayesian models, MCMC and GPU computation. Ranked #37 of 106 in Statistical Analysis Software by our editors (5.8/10); pricing: Free plan; best for bayesian modeling in R.

5.8/10★★★☆☆Editor score

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At a glance

• Editor score
  5.8 / 10
• Pricing
  Free plan
• Best for
  Bayesian modeling in R
• Free plan
  Yes
• Paid from
  Free
• Deployment
  Desktop
• Facts checked
  23 Sep 2026

• Where it wins

  • Write Bayesian models directly in native R code
  • Supports MCMC, optimisation, and TensorFlow CPU or GPU computation
  • Extensible with user-written R functions and packages

• Where it doesn't

  • Requires Python, TensorFlow, and TensorFlow Probability dependencies
  • Focused on Bayesian analysis rather than general statistical testing
  • Data import centers on R vectors, matrices, arrays, and data frames

Our verdict on greta

greta is an open-source R package for building and fitting Bayesian statistical models. It targets R users who need native-code model specification, from regression and hierarchical models to ecological and neural-network examples. Models use probability distributions, greta arrays, and model objects, then run through Markov chain Monte Carlo inference or optimisation. The package is available as a free plan and runs as desktop software on Windows, macOS, and Linux.

Its main strength is the depth of its R-native Bayesian workflow. Built-in distributions include normal, Poisson, categorical, and multivariate options, while documented examples cover linear, generalized, hierarchical, ecological, logistic, Poisson, and categorical regression. TensorFlow and TensorFlow Probability provide the computation layer, with CPU and GPU execution available. Greta arrays can convert R objects, and user-written R functions and packages extend the modeling environment. This makes greta a fit for solo, small, and mid-market teams already working in R and seeking flexible Bayesian model construction.

The trade-off is a narrow statistical focus. greta does not present itself as a general statistical testing environment, and its documented data conversion centers on R numeric or logical vectors, matrices, arrays, and numeric or logical data frames. Python, TensorFlow, and TensorFlow Probability are required dependencies, which should shape deployment planning. Choose greta when Bayesian modeling, MCMC, and programmable R workflows are the priority; choose a broader statistical analysis product when general-purpose testing or wider import coverage matters more.

Your product? Our editors can test greta in depth and publish a review, labelled as paid · from $149/mo →

greta pricing

greta fact sheet

Alternatives to greta

• RA free, programmable environment for statistical analysis, modeling, visualization, and data import.9.4
• SStataA broad, scriptable desktop environment for professional and reproducible applied analysis.9.3
• IBM SPSS StatisticsA broad desktop statistics suite with testing, modeling, forecasting, reporting, and R/Python integration.9.2

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Featured on iTechGuides

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

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Last updated 7 Oct 2026 · How we research and update