Bria 3.2

GPAI Provider: Bria AI

Metadata

Model URL: https://huggingface.co/briaai/BRIA-3.2
When was this model published? 2025-06-10
Is this a new or a fine-tuned model? New model
When was the Public Summary last updated? 2026-01-06
When did we evaluate the Public Summary? 2026-03-31 (see previous versions here)
Where did we find the Public Summary? We found this document linked on this page. An archived version can be found here.

Results of Evaluation

Section Transparency Usefulness General
Clarity Completeness Consistency Correctness Accessibility Comprehension Transparency Usefulness
Document 81.82 25.0 100.0 40.0 70.0 66.67 70.37 68.42
General information 81.25 60.26 100.0 71.43 N/A 92.86 69.73 92.86
Public Data Sources N/A 100.0 100.0 100.0 N/A N/A 100.0 N/A
Private Data Sources 100.0 100.0 100.0 100.0 N/A 100.0 100.0 100.0
Scraped/Crawled Data N/A 100.0 100.0 100.0 N/A N/A 100.0 N/A
User Data N/A 100.0 100.0 100.0 N/A N/A 100.0 N/A
Synthetic/Other Data N/A 100.0 100.0 100.0 N/A N/A 100.0 N/A
Data Processing 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0
Sum 90.59 79.76 100.0 90.82 88.0 96.3 86.97 94.74
Grades B+A

Evaluation Notes

If you update your public summary, please let us know so that we can update the evaluation and scores. We also welcome suggestions on improvements to this page, e.g. see FAQ section.

The public summary for the Bria 3.2 model is published by Bria AI on its website under the 'Security & Compliance' section, as a link to a PDF hosted on Google Drive. The summary closely follows the structure of the template, but provided contact details for the authorised representative and not for the company itself. The document also lacked some metadata such as version information and links to documentation. The summary describes training only involving licensed data, which requires relatively little disclosure through the template. We assessed its score as 86.97% with a grade of B+ for transparency, and 94.74% with a grade of A for usefulness.

Suggested Improvements
The following are the suggested improvements based on using our our methodology where the public summary had issues related to the specified metric. The severity represents the extent of the issue, with low indicating aspects that could be fixable, and high representing missing information or requiring major changes.

  • Document
    • M1 Document should clearly indicate whether it is the latest version or if it is outdated and a replacement is made available, as well as provide a link to all versions of the document. low
    • M2 Is a version for the document provided? high
    • M4 Document should have assured integrity, provide an authoritative source of the document, and have a correct date format. high
    • M5 Document should be provided in the same context as the model. medium
    • M6 Document should clearly indicate changes from previous version and where notice of updates or changes will be provided. medium
  • General information
    • M1 Contact details should refer to a non-generic contact point, and date (of latest data acquisition) should have the proper format. low
    • M2 No contact details provided for provider, no links to additional publicly available documentation.

      Languages covered by training data, as well as national, regional, and demographic specificities of training data not described. medium
    • M4 Provided information relating to the linguistic characteristics of the overall training data is not accurate. medium
    • M6 No indication of whether the model is continuously trained on new or dynamic data. low
  • Sum
    • M1 Document should clearly indicate whether it is the latest version or if it is outdated and a replacement is made available, as well as provide a link to all versions of the document.Contact details should refer to a non-generic contact point, and date (of latest data acquisition) should have the proper format. low
    • M2 Is a version for the document provided?No contact details provided for provider, no links to additional publicly available documentation.

      Languages covered by training data, as well as national, regional, and demographic specificities of training data not described. low
    • M4 Document should have assured integrity, provide an authoritative source of the document, and have a correct date format.Provided information relating to the linguistic characteristics of the overall training data is not accurate. low
    • M5 Document should be provided in the same context as the model. low
    • M6 Document should clearly indicate changes from previous version and where notice of updates or changes will be provided.No indication of whether the model is continuously trained on new or dynamic data. low

Previous Versions