Timestral
Intro
**Timestral** is a newly tracked term on FastToolHub's radar. Source signal: GitHub+HF+X. Radar summary: Mistral page: "Timestral: Mistral's time-series foundation models — State-of-the-art probabilistic forecasting in four sizes (5M–209M params), CPU-efficient, zero-shot ready." HF mistralai/Timestral-5M/28M/123M/209M (created Oct 14; 209M: 86 likes / 1.5k dl). HuggingPapers launch post (~13.7k impressions, RT by @ClementDelangue): "Mistral just released Timestral, a time series foundation model… with 21 quantiles and up to 32k context." Still on GH Hot Picks Oct 18 (mistralai/timestral, 279★).
Explain
Timestral appears in the model / AI-system category: something teams would load, call, or fine-tune rather than a pure UI gadget. Do not invent parameters, prices, or benchmarks beyond what the excerpt already states.
Usage
Start from the primary link: https://mistral.ai/news/timestral. If a GitHub repo is linked, skim README, license, and recent commits before integrating. For models: verify context length, license, and hardware needs from official docs; run a small smoke test before production. Numbers and claims in this page only repeat the radar excerpt — double-check upstream before publishing.