FreeLLMMistral AI launches Timestral, a time‑series foundation model family
Timestral offers four sizes up to 209 M parameters, achieving top zero‑shot scores on GIFT‑Eval, TIME and fev‑bench.
Four model sizes are available: 5 M, 28 M, 123 M and 209 M parameters, with the largest weighing 837 MB.
The models support past‑only, known‑future and categorical covariates, output 21 quantiles per step, and handle contexts up to 32,768 steps.
Inference runs on CPU or GPU using PyTorch, NumPy, safetensors and huggingface_hub; installation is via pip or a cloned repository.
What it means for you
Timestral provides a ready‑to‑use forecasting tool that works without a GPU, making advanced time‑series prediction accessible to researchers and developers on modest hardware. Its strong zero‑shot performance also offers a free alternative to commercial forecasting services for those seeking locally runnable models.
Sources
- mistralai/timestral: Repository for Timestral, the time-series foundation model by Mistral AI, GitHub trending (official), 15 Oct 2026
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