Gradistat V 91 Free May 2026

In the world of sedimentology, geomorphology, and soil science, few software tools have achieved the legendary status of Gradistat. Specifically, Gradistat v 9.1 free remains one of the most widely searched and downloaded pieces of software in the geosciences, even years after its last official update.

Why? Because grain size analysis is fundamental. Whether you are analyzing beach sands, river sediments, glacial tills, or deep-sea cores, you need to convert raw sieve data and hydrometer measurements into meaningful statistical parameters: mean, sorting (standard deviation), skewness, and kurtosis. Gradistat v 9.1 does this efficiently, accurately, and—crucially—for free.

This article provides everything you need to know: what Gradistat v 9.1 is, its key features, how to get it legally for free, how it compares to modern alternatives, and a step-by-step guide to using it.


Because the original v 9.1 is no longer supported, the geoscience community has created "forks" and improvements: gradistat v 91 free

If you need a pure free experience but want modern stability, the Gradistat 9.1 macro can still be copied to a new .xlsm file – an advanced but doable project.


You will see:

Despite its popularity, users report recurring problems: In the world of sedimentology, geomorphology, and soil

The software computes up to 14 statistical parameters using three different methods:

1. The User Interface (Circa Windows 95) Prepare for pain. The UI is purely functional:

2. Data Size Limitations Because it’s a 32-bit legacy application, v9.1 Free struggles with modern big data: Because the original v 9

3. No Help File in the Free Version The free distribution often strips out the manual. You are left with a single readme.txt that assumes you already know the difference between "Gaussian response" and "Hofker's method." New users will be lost.

4. "v9.1" – Where are the updates? The last stable free release was archived around 2008. It does not support 64-bit natively (though runs via compatibility mode). It does not support Unicode – your species names must be ASCII only.

  • Skewness: positive (fine skewed) vs. negative (coarse skewed) distributions suggest depositional processes or post-depositional reworking.
  • Kurtosis: peaked vs. flat distributions; sensitive to tails and sample size.
  • Grain-size distribution analyses:
  • Standard methods implemented: Folk & Ward (1957), Trask (1932), graphical methods (e.g., cumulative curves), and moment method. Options to switch between protocols or report multiple methods for comparison.
  • Export and reporting: export tables and plots to common formats (CSV, TXT, PNG) and generate printable summary reports.
  • Batch processing: apply analyses across multiple samples and compile comparative tables and plots.
  • Quality control: error checking for inconsistent input (non-monotonic cumulative percentages, negative sizes), and warnings for small sample sizes that can bias statistics.
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