Ministral 3

Ministral 3

Mistral AI
Timestral

Timestral

Mistral AI
+
+

Related Products

  • LM-Kit.NET
    29 Ratings
    Visit Website
  • LTX
    182 Ratings
    Visit Website
  • Google AI Studio
    41 Ratings
    Visit Website
  • Gemini Enterprise Agent Platform
    1,161 Ratings
    Visit Website
  • ONLYOFFICE Docs
    715 Ratings
    Visit Website
  • RaimaDB
    12 Ratings
    Visit Website
  • Innoslate
    98 Ratings
    Visit Website
  • Nexo
    18,780 Ratings
    Visit Website
  • Fraud.net
    56 Ratings
    Visit Website
  • IONOS Cloud GPU Servers
    45,340 Ratings
    Visit Website

About

Mistral 3 is the latest generation of open-weight AI models from Mistral AI, offering a full family of models, from small, edge-optimized versions to a flagship, large-scale multimodal model. The lineup includes three compact “Ministral 3” models (3B, 8B, and 14B parameters) designed for efficiency and deployment on constrained hardware (even laptops, drones, or edge devices), plus the powerful “Mistral Large 3,” a sparse mixture-of-experts model with 675 billion total parameters (41 billion active). The models support multimodal and multilingual tasks, not only text, but also image understanding, and have demonstrated best-in-class performance on general prompts, multilingual conversations, and multimodal inputs. The base and instruction-fine-tuned versions are released under the Apache 2.0 license, enabling broad customization and integration in enterprise and open source projects.

About

Timestral is a family of time-series foundation models and a Python inference package for generating multivariate probabilistic forecasts from historical sequences. The four model sizes (5M, 28M, 123M and 209M parameters) support past-only, known-future and categorical covariates, return quantile forecasts, and accept context windows up to 32,768 time steps. Developers can load pretrained weights from the Hugging Face Hub or from local files and run inference on CPU or GPU, then incorporate forecasts into monitoring, capacity-planning, energy, supply-chain, financial-risk, or maintenance workflows. Timestral supports zero-shot forecasting and can be adapted to domain data through Mistral Forge. The package is intended for data scientists, machine-learning engineers, and teams building forecasting systems; repository code is Apache 2.0, while model weights use a separate Modified MIT license.

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Supported
iPad Supported
Android Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Not Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

Developers, AI engineers, and enterprises wanting a solution offering a model that can scale from edge devices to large-scale cloud deployments

Audience

Data scientists, machine-learning engineers, forecasting practitioners, and teams developing time-series forecasting systems.

Support

Phone Support Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

No images available

Pricing

Free
Free Version Supported
Free Trial Supported

Pricing

No information available.
Free Version Supported
Free Trial Not Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation Supported
Webinars Not Supported
Live Online Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Mistral AI
Founded: 2023
France
mistral.ai/news/mistral-3

Company Information

Mistral AI
Founded: 2023
France
github.com/mistralai/timestral

Alternatives

Mistral Small 4

Mistral Small 4

Mistral AI

Alternatives

TimesFM-3

TimesFM-3

Google
Mistral Large 3

Mistral Large 3

Mistral AI
Qwen3.5

Qwen3.5

Alibaba
Pixtral Large

Pixtral Large

Mistral AI
Solar Mini

Solar Mini

Upstage AI
Inkling

Inkling

Thinking Machines Lab
Mistral NeMo

Mistral NeMo

Mistral AI

Categories

Categories

AI Models Supported

Integrations

Mistral Forge Not Supported
NexaSDK Supported
Oxlo.ai Supported

Integrations

Mistral Forge Supported
NexaSDK Not Supported
Oxlo.ai Not Supported
Claim Ministral 3 and update features and information
Claim Ministral 3 and update features and information
Claim Timestral and update features and information
Claim Timestral and update features and information