Free AI Model Card Generator
Create a model card or system card that documents your AI for the people who review, buy, or govern it, using language aligned with the NIST AI Risk Management Framework 1.0 and the EU AI Act. Fill a short guided form, generate the card, then download it as Word, PDF, or Markdown. It is free and needs no sign-up. Your details are processed securely to write the card and are never stored, sold, or used for training.
An AI model card, or system card, is a short structured document that tells anyone using an AI model what they need to know to use it responsibly: its intended and out-of-scope uses, the data behind it, measured performance, fairness testing, and known limitations. This free tool turns a guided form into a finished card worded to line up with the NIST AI RMF 1.0 and the EU AI Act transparency requirements, as Word, PDF, or Markdown, with no paywall and no sign-up.
Model card details
Fill in what you know. The tool writes a complete model card from your details, structured by the NIST AI RMF 1.0 MAP and MEASURE functions, ready to download as Word, PDF, or Markdown.
Model details
Purpose and scope
Data and performance
Evaluation and limitations
Your model card will appear here. Fill in the details on the left and select Generate card.
How the AI model card generator works
Describe your model
Enter the model name, owner, and version, then fill the guided fields for intended use, training data, performance, evaluation, and limitations.
Generate your model card
The tool writes a card from your details, structured by the NIST AI RMF 1.0 MAP and MEASURE functions and tagged with control IDs. Results come back in seconds.
Download or copy
Export the card as a PDF, an editable Word file, or Markdown, or copy it as Markdown, then have it reviewed by a technical reviewer and legal or compliance counsel before you publish it.
Free, private, and built on NIST AI RMF 1.0 and the EU AI Act
Most model-card tools sit behind a lead form or keep a copy of what you enter. This one asks for no sign-up and keeps nothing. Writing a card needs a language model, so your details are sent to our server and processed there, then discarded. The sections come from the MAP and MEASURE functions of the NIST AI Risk Management Framework 1.0 and are worded to support the technical-documentation and transparency obligations of the EU AI Act.
We built this from our own AI governance programme, not from a summary of the standard: see BlockSurvey's AI Policy for how we apply the same practices to ourselves.
Processed, never kept
Your details are processed securely to write the card and are never stored, sold, or used for training. Keep the form to model-level documentation and leave secrets, personal data, and PHI out.
No account required
No sign-up, no email wall, no tracking of what you document.
Free, real download
The complete card as Word, PDF, or Markdown at no cost, not a watermarked sample.
What the model card includes
Eight sections, each tagged with the matching NIST AI RMF 1.0 control ID where one applies:
- Model details, name, owner or provider, and version.
- Intended use and users, so the card states who the model is for (MAP 1.1).
- Out-of-scope and prohibited uses, so misuse is named explicitly.
- Training data and provenance, sources, rights to use, and known quality limits (MAP 2.3).
- Performance, the metrics, datasets, and conditions the model was measured under.
- Evaluation and fairness testing across affected groups (MEASURE 2.11).
- Explainability and known limitations, so decisions can be explained (MEASURE 2.9).
- A review-and-disclaimer note, carried inside the generated document.
How each section maps to the framework
A model card is where the NIST AI RMF and the EU AI Act overlap in practice: the same fields that make a model reviewable are the ones both ask you to document. This is how the card's sections line up.
| Card section | NIST AI RMF 1.0 | EU AI Act |
|---|---|---|
| Intended use and users | MAP 1.1, context and intended purpose are established. | Transparency: the intended purpose must be documented for high-risk systems. |
| Training data and provenance | MAP 2.3, data sources, quality, and provenance are documented. | Technical documentation: data governance and datasets used for training. |
| Evaluation and fairness testing | MEASURE 2.11, bias and disparate impact are tested across groups. | Technical documentation: testing procedures and results, including bias. |
| Explainability and limitations | MEASURE 2.9, model behaviour and limitations are documented. | Transparency: capabilities, limitations, and human-oversight measures. |
Built for every team working with AI
Whether you train models or integrate someone else's, a model card is the artifact a reviewer, a buyer, or a regulator asks for first. This generator gives you a dated starting point, and it pairs well with an AI survey platform when the data behind those models comes from people.
ML & data science teams
Ship a model card with every model, without writing the structure from scratch each time.
Compliance & privacy teams
Produce the transparency artifact the EU AI Act expects for high-risk systems.
Legal & risk
See intended use, limitations, and data provenance stated in one reviewable place.
Product & engineering
Document what a system can and cannot do before it ships, not after an incident.
Vendors selling into enterprise
Hand buyers a clear system card that answers their AI due-diligence questions.
Researchers & open-source authors
Publish a Markdown model card next to your weights or repository in seconds.
Documenting data provenance for your model?
The training-data provenance section you just filled (MAP 2.3) is only as trustworthy as the tools you collect data with. BlockSurvey is an AI survey platform, encrypted end to end, with a published AI policy you can cite in your own model card, so responses are never sold, mined, or used to train models.