Stata Editions

Whether you’re an experienced statistician or a first-year student:
Stata offers the right edition for every user.

Basic Edition for medium-sized datasets

With Stata BE, you can analyze datasets with up to 2,048 variables. The number of observations is limited only by the amount of RAM available on your computer. Stata BE can process a maximum of 798 independent variables in a model.

Standard Edition for larger datasets

Stata SE and Stata BE differ primarily in the size of the datasets that can be analyzed. Stata SE can process datasets with up to 32,767 variables and a maximum of 10,998 independent variables in a model.

High-Performance Edition for the largest datasets

Stata MP is the most powerful edition of Stata and is optimized for particularly computationally intensive analyses on multi-core and multiprocessor systems. With Stata MP, you can analyze datasets with up to 65,532 variables and estimate models with up to 120,000 independent variables.

Target Group

Small to medium-sized datasets

Larger datasets, professional analyses

Very large datasets, high computational load

Parallel processing

❌ No

❌ No

✅ Yes (Multi‑Core / Multi‑CPU)

Maximum variables (dataset)

2.048

32.767

120.000

Max. independent variables (model)

798

10.998

65.532

Number of observations

Up to approx. 2.14 billion

Up to approx. 2.14 billion

Up to approx. 20 billion (hardware-dependent)

Processing speed

▮▮▮▮
(solid)

▮▮▮▮▮▮▮
(high)

▮▮▮▮▮▮▮▮▮▮
(very high, scales with the number of cores)

Performance through parallelization

–

–

▮▮▮▮▮▮▮▮▮▮
(very high)

Typical applications

Studies, teaching, compact analyses

Everyday use in research & practice

Computationally intensive models, simulations, large research projects

Functional scope

Full

Full

Full

All of the editions listed above offer the same full functionality and include PDF documentation. All editions are fully compatible with each other. Do-files and data can be exchanged without modification.

Comparison of limits

Performance of Stata/MP
Speed on multiple cores compared with speed on a single core.

Stata/MP for multiprocessor systems

Stata/MP is the High Performance Edition of Stata and makes optimal use of modern multi-core processors. The software is available in license variants from Stata/MP2 to Stata/MP64 and supports up to 2, 4, 8, 16, 32, or 64 processor cores, depending on the license. This allows performance to be flexibly adapted to different hardware, from laptops to high-performance servers.

Stata/MP is the fastest and most powerful version of Stata. On dual-core systems, Stata/MP is on average around 40% faster than Stata/SE. For computationally intensive estimation methods, speedups of up to 72% are possible. Performance scales with the number of available processor cores and provides significant speed gains, particularly on multi-core and multiprocessor systems.

Stata/MP can process large datasets with up to 120,000 variables and supports models with up to 65,532 independent variables. This makes the software ideal for large-scale research projects, complex statistical models, and demanding data analyses.

More information about Stata/MP: Stata/MP Performance Report (PDF)

System Requirements

Stata for Windows

  • Windows 11*
  • Windows 10*
  • Windows Server 2025, 2022, 2019, 2016, 2012R2*

* 64-bit for x86-64 from Intel® and AMD

Stata for Mac

  • Mac with Intel processor or Apple Silicon
  • macOS 11 (Big Sur) to
  • macOS 26 (Tahoe) for Macs with Apple Silicon and
    macOS 10.13 (High Sierra) to macOS 26 (Tahoe) for Macs with Intel processors

Stata for Linux

  • 64-bit (x86-64)
  • Minimum requirements include the GNU C Library (glibc) 2.28 or higher and libcurl4
  • GTK 2.24 must be installed for xstata

Hardware Requirements

  • At least 1 GB RAM for BE, 2 GB RAM for SE, 4 GB RAM for MP
  • At least 4 GB of disk space
  • Stata for Unix requires a graphics card capable of displaying thousands of colors or more (16-bit or 24-bit color depth)

Hardware recommendations for dual-core, multi-core, or multiprocessor computers

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