Timestral Tested: How Much Data AI Demand Forecasting Needs

A hands-on benchmark of Mistral's Timestral (released 15 October 2026) against Chronos-2, TimesFM, t0-gamma, LightGBM and spreadsheet AutoETS on 300 Online Retail II products and GB national electricity demand found the pretrained models tied on retail and beat both baselines, with Timestral's error 3% below LightGBM and 14% below AutoETS. Timestral needed about two days of half-hourly demand or eight weeks of weekly sales to beat repeating the last value, and every pretrained model forecast "another August" through November when given only summer grid history, while a small temperature-response model had less than a third of their error. The author notes licence limits (Timestral free only under $20M monthly revenue) and open questions about training-data leakage.