Codestral Mamba

Codestral Mamba

Mistral AI
Timestral

Timestral

Mistral AI
+
+

Related Products

  • Google AI Studio
    41 Ratings
    Visit Website
  • Gemini Enterprise Agent Platform
    1,161 Ratings
    Visit Website
  • Retool
    598 Ratings
    Visit Website
  • Careerminds
    46 Ratings
    Visit Website
  • AnalyticsCreator
    46 Ratings
    Visit Website
  • LM-Kit.NET
    29 Ratings
    Visit Website
  • LTX
    182 Ratings
    Visit Website
  • RealEstateAPI (REAPI)
    58 Ratings
    Visit Website
  • Thinfinity Workspace
    16 Ratings
    Visit Website
  • Innoslate
    98 Ratings
    Visit Website

About

As a tribute to Cleopatra, whose glorious destiny ended in tragic snake circumstances, we are proud to release Codestral Mamba, a Mamba2 language model specialized in code generation, available under an Apache 2.0 license. Codestral Mamba is another step in our effort to study and provide new architectures. It is available for free use, modification, and distribution, and we hope it will open new perspectives in architecture research. Mamba models offer the advantage of linear time inference and the theoretical ability to model sequences of infinite length. It allows users to engage with the model extensively with quick responses, irrespective of the input length. This efficiency is especially relevant for code productivity use cases, this is why we trained this model with advanced code and reasoning capabilities, enabling it to perform on par with SOTA transformer-based models.

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 Not Supported
iPad Not Supported
Android Not 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 and anyone in search of an AI language model to generate code

Audience

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

Support

Phone Support Not 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 Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

No images available

Pricing

Free
Open source
Free Version Supported
Free Trial Not 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 Not Supported
In Person Not Supported

Training

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

Company Information

Mistral AI
France
mistral.ai/news/codestral-mamba/

Company Information

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

Alternatives

Mistral Code

Mistral Code

Mistral AI

Alternatives

TimesFM-3

TimesFM-3

Google
Falcon Mamba 7B

Falcon Mamba 7B

Technology Innovation Institute (TII)
Solar Mini

Solar Mini

Upstage AI
Jamba

Jamba

AI21 Labs
Mistral NeMo

Mistral NeMo

Mistral AI

Categories

AI Code Generators Supported
AI Coding Models Supported
AI Models Supported
Foundation Models Supported

Categories

AI Models Supported

Integrations

APIPark Supported
Clojure Supported
Continue Supported
Deep Infra Supported
EvalsOne Supported
Graydient AI Supported
HTML Supported
Klee Supported
Literal AI Supported
Mammouth AI Supported
Microsoft Foundry Agent Service Supported
Nutanix Enterprise AI Supported
OpenLIT Supported
OpenPipe Supported
PromptPal Supported
Ragas Supported
SydeLabs Supported
Unify AI Supported
Visual Basic Supported
Yaseen AI Supported

Integrations

APIPark Not Supported
Clojure Not Supported
Continue Not Supported
Deep Infra Not Supported
EvalsOne Not Supported
Graydient AI Not Supported
HTML Not Supported
Klee Not Supported
Literal AI Not Supported
Mammouth AI Not Supported
Microsoft Foundry Agent Service Not Supported
Nutanix Enterprise AI Not Supported
OpenLIT Not Supported
OpenPipe Not Supported
PromptPal Not Supported
Ragas Not Supported
SydeLabs Not Supported
Unify AI Not Supported
Visual Basic Not Supported
Yaseen AI Not Supported
Claim Codestral Mamba and update features and information
Claim Codestral Mamba and update features and information
Claim Timestral and update features and information
Claim Timestral and update features and information