Forum Discussion
Model Training Data Last Updated Date
The October 2023 date is the model’s training data cutoff — that’s the latest point it has knowledge of.
The May 2024 date in Azure just means when the model package was last updated or published, not when new data was added.
So even though your deployment shows a recent version (2025-04-14), the model itself still only knows up to October 2023.
Of course! It's a very fair and important question. And you're not the only one noticing these discrepancies.
Perhaps something similar is happening:
When you see "Last training data update: May 2024" in Azure AI Foundry, this refers to the most recent time at which any part of the model (including tweaks and system updates) was incorporated with new data or corrected. This can include minor tweaks, performance improvements, alignment adjustments, etc., made after the initial training phase, but not necessarily a complete retraining with new data.
On the other hand, if you ask the deployed GPT-4.1-nano model about its training deadline and get an answer like "October 2023," that refers to the primary dataset originally used for training. This represents the bulk of the main network of knowledge data, books, documentation, etc., and it's not something that changes easily or frequently.
In short:
"May 2024" refers to the deployment or update version (similar to a software patch) of the model.
"October 2023" refers to the actual knowledge boundary that the model "knows."
If your application relies on up-to-date factual knowledge (news, trends, technology updates, etc.), the October 2023 boundary is what really matters. Even if the deployment was recent, the model's understanding of the world likely hasn't changed unless it's adjusted with more recent data (which is usually clearly stated).
Summary: This isn't a misunderstanding. Azure "update" dates don't mean the model was trained on data up to that point. They typically reflect the last build of the model, not the actual knowledge boundary.
Great explanation. Thanks!