GPAI Training Transparency

Quality Assessment AI Act Article 53(1)(d) Public Summaries

The AI Act's Article 53(1)(d) requires General-Purpose AI (GPAI) model providers to publish "a sufficiently detailed summary about the content used for training ... according to a template provided by the AI Office". Enforcement on this has started from 2nd August 2026. The AI Office is currently investigating compliance regarding public summaries as reported by Euractiv with non-compliance risking fines.

To support this, we discovered 78 public summaries, which we evaluate across two aspects: Transparency and Usefulness and assign a score using our developed methodology. Our findings expose challenges regarding accessibility, vagueness and incompleteness of information, and limitations this poses on rightsholders. We also highlight missing summaries for 46 models based on our preliminary analysis. Please get in touch if you find any summaries or would like to know more about our work.

See our peer-reviewed article: Dick A. H. Blankvoort, Harshvardhan J. Pandit, and Maximilian Gahntz (2026). Quality Assessment of Public Summary of Training Content for GPAI models required by AI Act Article 53(1)(d). 9th ACM Conference on Fairness, Accountability, and Transparency (FAccT), Montreal, Canada. Zenodo. DOI:10.1145/3805689.3806755

Media Coverage:
Euractiv "AI labs at odds with EU over half-hearted data disclosures (7 Aug 2026)
Euractiv "Researchers have trouble finding AI training data summaries (2 Mar 2026);
Tech Policy Press "How Big AI Developers are Skirting a Mandate for Training Data Transparency (4 Mar 2026).

The table below shows an overview evaluated public summaries with A+ as the highest grade score and F the lowest. You can also click on the columns to sort the table by name or by score. A separate list is provided further below with published summaries currently being evaluated, and another list for models which require a public summary is missing despite being necessary. You can click the model name to go to the detailed evaluation page which has more information, a link to the summary, and our evaluation notes. See detailed overview with scores for each section of the public summary. The list of summaries provides links to all found summaries.

Evaluated Public Summaries

Model Provider Transparency Usefulness
Baguettotron and Monad Pleias Pleias A+ A+
Pleias 1.0 Pleias Pleias A   A+
Apertus Swiss AI Initiative Swiss AI Initiative A   A+
Luciole Base OpenLLM France OpenLLM France A   A+
FIBO Bria AI Bria AI B+ A+
Luciole Instruct 1.1 OpenLLM France OpenLLM France A   A  
Bria 3.2 Bria AI Bria AI B+ A  
SmolLM3-3B HuggingFace HuggingFace B+ B+
Domyn Large Domyn Domyn B+ B+
Bielik v3 11B Instruct SpeakLeash SpeakLeash B+ C+
PLLuM-12B-base-2512 Ministry of Digital Affairs of Poland Ministry of Digital Affairs of Poland B+ C+
Adobe Firefly Adobe Adobe C+ B+
Nemotron 3 and 3.5 Family NVIDIA NVIDIA C+ C+
Inkling Thinking Machines Thinking Machines C+ C+
Inkling Small Thinking Machines Thinking Machines C+ C+
FLUX.3 Black Forest Labs Black Forest Labs B   C  
Nova 2 Lite Amazon Amazon C+ C+
Nemotron Nano 12B v2 NVIDIA NVIDIA C+ C+
FastwebMIIA Fastweb Fastweb C   C+
MAI Cyber 1 Flash Microsoft Microsoft C+ C  
MAI Code 1.1 Flash Microsoft Microsoft C+ C  
Minimax M3 Minimax Minimax C+ D+
MAI Code 1 Flash Microsoft Microsoft C+ C  
MAI-Image-2.5 Microsoft Microsoft C+ D+
Ministral 3 14B Mistral AI Mistral AI C   C  
Ministral 3 8B Mistral AI Mistral AI C   C  
Ministral 3 3B Mistral AI Mistral AI C   C  
MAI-Image-2 Microsoft Microsoft C+ D+
Apertus v1.5 Swiss AI Initiative Swiss AI Initiative C   C+
GPT-5.6 Luna OpenAI OpenAI C+ D+
GPT-5.5 OpenAI OpenAI C+ D+
GPT-6 Astra OpenAI OpenAI C+ D+
GPT-5.2 OpenAI OpenAI C+ D+
Grok Voice Think Fast xAI xAI C+ D+
Hy3 Tencent Tencent C+ C  
GPT Images 2.0 OpenAI OpenAI C+ D+
GPT-5.4 Nano OpenAI OpenAI C+ D+
Gemma 4 Google Google C   C  
Gemini 3 Pro Google Google C   C  
Mistral Small 4 Mistral AI Mistral AI C   C  
Mistral Large 3 Mistral AI Mistral AI C   C  
Grok 4.5 xAI xAI C   C  
Mythos 5.1 / Fable 5.1 Anthropic Anthropic C   D+
Command A+ Cohere Cohere C   C  
Claude Opus 5 Anthropic Anthropic C   D+
Claude Opus 4.8 Anthropic Anthropic C   D+
Claude Mythos 5 / Claude Fable 5 Anthropic Anthropic C   D+
Claude Mythos Preview Anthropic Anthropic C   D+
Claude Sonnet 5 Anthropic Anthropic C   D+
Claude Opus 4.7 Anthropic Anthropic C   D+
Muse Image Meta Meta C   D+
Muse Glimmer Meta AI Meta AI C   D+
Muse Spark Meta Meta C   D+
Phi 4 Reasoning Vision 15B Microsoft Microsoft C+ D  
Seed 2.0 Pro ByteDance ByteDance C   D+
Seedance 2.5 ByteDance ByteDance C   D  
Seedance 2.0 ByteDance ByteDance D+ D  
Seedream 5.0 Pro ByteDance ByteDance D+ D  
Midjourney Image and Video family of models Midjourney Midjourney D   D+
DeepSeek-V4 DeepSeek DeepSeek D+ D+
Phi-4 Microsoft Microsoft D   F  

Summaries currently being evaluated

We are currently evaluating 17 public summaries. Their scores and our notes will be published shortly. In the meantime, you can access the public summary through the details page by clicking the model name.

Model Provider
MAI-Image-2.6 Microsoft Microsoft
Claude Opus 5.5 Anthropic Anthropic
Phi-3.5 Vision Instruct Microsoft Microsoft
MAI-DS-R1 Microsoft Microsoft
MAI Thinking 1 Microsoft Microsoft
Phi-4 Reasoning Microsoft Microsoft
Phi-MoE Microsoft Microsoft
ChatGPT Images 2.5 Flare OpenAI OpenAI
Phi-1.5 Microsoft Microsoft
Phi-4 Multimodal Instruct Microsoft Microsoft
Phi-1 Microsoft Microsoft
Phi-2 Microsoft Microsoft
Magma-8B Microsoft Microsoft
Phi-3 Microsoft Microsoft
Minimax H3 Minimax Minimax
Phi-4 Mini Instruct Microsoft Microsoft
PLLuM-12B-instruct-2512 Ministry of Digital Affairs of Poland Ministry of Digital Affairs of Poland

Models with missing summaries

Based on our preliminary analysis, we have assessed the following models as requiring a mandatory public summary, but which we could not discover.

Model Provider
Granite 4.1 Vision IBM IBM
DiffusionGemma 26B A4B IT Google Google
Gemini Robotics 1.5 Google Google
Gemini 3.5 Flash Cyber Google Google
Veo 3.1 Google Google
Gemini Omni Google Google
Nova 2 Sonic Amazon Amazon
Devstral Small Mistral Mistral
Gemini Flash 3.1 Lite Google Google
North Mini Code 1.0 Cohere Cohere
Gemini 3.6 Flash Google Google
Gemini 2.5 Flash Image Google Google
Claude Opus 4.6 Anthropic Anthropic
FLUX.2 [max] Black Forest Labs Black Forest Labs
Velvet 2B Speech Almawave Almawave
FLUX.2 [pro] Black Forest Labs Black Forest Labs
Gemini Robotics ER 1.5 Google Google
GPT-5.6 Terra OpenAI OpenAI
Palmyra X6 WRITER WRITER
FLUX.2 Klein Black Forest Labs Black Forest Labs
Devstral 2 Mistral Mistral
Claude Sonnet 4.5 Anthropic Anthropic
Imagen 4 Fast Google Google
Claude Opus 4.5 Anthropic Anthropic
Velvet 25B Almawave Almawave
FLUX.2 [dev] Black Forest Labs Black Forest Labs
VITRA Microsoft Microsoft
Granite 4.2 IBM IBM
GPT-5.6 Sol OpenAI OpenAI
Apriel 1.5 15B Thinker ServiceNow ServiceNow
Claude Opus 4.1 Anthropic Anthropic
GPT-OSS OpenAI OpenAI
Sora 2 OpenAI OpenAI
Gemini Robotics ER 1.6 Google Google
Gemini 3.7 Flash Google Google
Gemini Robotics ER 2 Google Google
FIBO 1.5 Bria AI Bria AI
Granite 4.1 IBM IBM
Granite 4.0 H IBM IBM
Palmyra X5 WRITER WRITER
Velvet 2B 1.5 Almawave Almawave
Claude Sonnet 4.6 Anthropic Anthropic
Gemini 3.5 Flash Lite Google Google
Tiny Aya Base Cohere Cohere
North Micro Vision Instruct Cohere Cohere
Claude Haiku 4.5 Anthropic Anthropic

Why we started this project:

  • We contend that compliance cannot be fait accompli, and that the public summaries are a key factor in creating transparency and enabling rights enforcement. Towards this, our work also acts as a guide for providers who are yet to publish their summaries to consider how to do so with the highest possible quality and utility.
  • Compliance also invites practices that are intentionally or unintentionally deficient in achieving the goals. Our work serves as a useful tool for describing how and where and why certain practices are 'bad', e.g., where they use obfuscation, do not provide stated information. Using this, we can detect trends or patterns in whether the same issues occur in many summaries, and if so, how they can be collectively addressed through guidance, or enforced with priority.
  • The largest challenge in undertaking this work has been finding public summaries as there is no consistent format or practice for how they should be provided. For this, we provide recommendations.
  • The template for public summaries provided by the AI Office is intended to be revised with time to improve the state of documentation as well as to better guide the providers. We also provide recommendations for these to improve the quality and accessibility of the public summaries.