TabPFN-3.5-Thinking sets the new bar
When you’re forecasting electricity prices for the next bid or deciding how much stock to buy for the holiday season, better predictions can have significant business value. TabPFN-3.5-Thinking uses more compute during training and is made for tasks where greater accuracy is worth the investment.
We are upgrading Thinking mode to outperform every other foundation or traditional model available on the market, now on datasets with up to 1,000,000 rows. New Thinking also entirely defines the Pareto frontier: for every other method there is a Thinking variant that is both more accurate and faster to train.
The update starts rolling out next week. Interested? Sign up now for early access and extra API credits to test.
More accurate predictions, at a larger scale
TabPFN-3.5 already supports up to 1M rows. Today, we bring Thinking to the same scale, up from its previous limit of 200k rows. For energy trading, that means using more observations of price and demand on the market. For retail stock planning, it means learning from more patterns across products, stores and promotions.
And it shows on the BeyondArena-large, covering datasets with 100k to over 1M training rows. TabPFN-3.5-Thinking has a winrate of 95.2% (max) against RealMLP, the previous #1 model. It also beats Kumo-Tabular with a winrate of 93.0% (medium), and even outperforms our own TabPFN-3.5-Plus.
We also optimized the latency. TabPFN-3.5-Thinking mode now entirely defines the Pareto frontier: for every other method there is a Thinking variant that is both more accurate and faster to train. On large-data tasks, Thinking mode takes 32% less prediction time than the previous version. If you are predicting on large volumes, that means less time waiting and more time to act.
Account for patterns across customers, products and time
The outcome of churn, revenue or a price can depend on the customer, product or device. People also often spend more during a promotion or bonus period, customers might churn after a period of inactivity, and Christmas might increase the demand for a particular product group. This is grouped and temporal data.
Now, TabPFN-3.5-Thinking is the best model for predictions on every type of data - from grouped, to temporal, high-cardinality and high-dimensionality. We measured the performance on BeyondArena, and it consistently took first place on every data subslice, beating the closest rivals - both classic machine learning models like RealMLP and other tabular foundation models.
All in all, Thinking gives you a better basis for planning around the customers, products and periods that matter to your business.
Try the new TabPFN-3.5-Thinking
The new Thinking will be API-exclusive at launch, rolling out from next week onwards, with private deployments following soon for select enterprise customers.
Interested? Sign up now for early access and extra API credits to test, and reach out to us if you’d like to be a part of our enterprise offering.
