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Description

Timestral represents a suite of time-series foundation models along with a Python inference toolkit designed to create multivariate probabilistic forecasts based on historical data sequences. It comes in four different model sizes—5M, 28M, 123M, and 209M parameters—that are capable of handling past-only, known-future, and categorical covariates, providing quantile forecasts while accommodating context windows as extensive as 32,768 time steps. Users have the flexibility to load pretrained weights either from the Hugging Face Hub or directly from local files, enabling them to perform inference on both CPU and GPU. Such forecasts can be seamlessly integrated into various applications, including monitoring systems, capacity planning, energy management, supply chain logistics, financial risk assessment, or maintenance operations. Furthermore, Timestral offers zero-shot forecasting capabilities and can be tailored to specific domain data through the Mistral Forge. This package is primarily aimed at data scientists, machine learning engineers, and collaborative teams focused on developing robust forecasting solutions; the repository code is licensed under Apache 2.0, while the model weights are governed by a separate Modified MIT license. With its comprehensive features, Timestral is positioned to significantly enhance the accuracy and efficiency of predictive analytics in numerous industries.

Description

WeatherNext represents a suite of AI-driven models developed by Google DeepMind and Google Research, designed to deliver cutting-edge weather predictions. These advanced models surpass conventional physics-based approaches in both speed and efficiency, leading to enhanced reliability in forecasts. By improving the accuracy of weather predictions, these innovations could significantly aid in disaster preparedness, ultimately saving lives during severe weather scenarios and bolstering the dependability of renewable energy sources and supply chains. WeatherNext Graph stands out by providing more precise and efficient deterministic forecasts than existing systems, producing a single forecast for each specified time and location with a 6-hour temporal resolution and a 10-day lead time. In addition, WeatherNext Gen excels at generating ensemble forecasts that outshine the current predominant models, thereby equipping decision-makers with a clearer understanding of weather uncertainties and the associated risks of extreme weather conditions. This leap in forecasting capability promises to transform how we respond to and manage the impacts of climate variability.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

No images available

Screenshots View All

Integrations

AlphaCode No 
AlphaEvolve No 
AlphaFold No 
Chinchilla No 
Gemini No 
Gemini Deep Research No 
Gemini Diffusion No 
Gemini Enterprise No 
Gemini Enterprise Agent Platform No 
Gemini Robotics No 
GitHub No 
Google AI Studio No 
Google Cloud BigQuery No 
Google Cloud Platform No 
Google Earth Engine No 
Gopher No 
Mistral Forge Yes 
Music AI Sandbox No 
Project Mariner No 

Integrations

AlphaCode Yes 
AlphaEvolve Yes 
AlphaFold Yes 
Chinchilla Yes 
Gemini Yes 
Gemini Deep Research Yes 
Gemini Diffusion Yes 
Gemini Enterprise Yes 
Gemini Enterprise Agent Platform Yes 
Gemini Robotics Yes 
GitHub Yes 
Google AI Studio Yes 
Google Cloud BigQuery Yes 
Google Cloud Platform Yes 
Google Earth Engine Yes 
Gopher Yes 
Mistral Forge No 
Music AI Sandbox Yes 
Project Mariner Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based No 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person Yes 

Vendor Details

Company Name

Mistral AI

Founded

2023

Country

France

Website

github.com/mistralai/timestral

Vendor Details

Company Name

Google DeepMind

Founded

2010

Country

United Kingdom

Website

deepmind.google/science/weathernext/

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Product Features

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