Timestral launches time-series forecasting models
Mistral AI: Introducing Timestral
State-of-the-art probabilistic forecasting in four sizes (5M–209M params), CPU-efficient, zero-shot ready.
Get smart on it
Timestral is a family of time-series foundation models designed to forecast patterns in data that changes over time, such as sensor readings or financial metrics. The largest model contains 209 million parameters and ranks first on the field's main public benchmarks while using fewer parameters than competing models. Time-series forecasting matters because enterprises rely on these predictions to make decisions about capacity planning, maintenance, energy use, and supply chains. Unlike traditional forecasting models that are trained separately for each dataset, foundation models like Timestral are pre-trained on diverse data and can forecast accurately on new domains without additional training.
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