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Description

The Gemma family consists of advanced, lightweight models developed using the same innovative research and technology as the Gemini models. These cutting-edge models are equipped with robust security features that promote responsible and trustworthy AI applications, achieved through carefully curated data sets and thorough refinements. Notably, Gemma models excel in their various sizes—2B, 7B, 9B, and 27B—often exceeding the performance of some larger open models. With the introduction of Keras 3.0, users can experience effortless integration with JAX, TensorFlow, and PyTorch, providing flexibility in framework selection based on specific tasks. Designed for peak performance and remarkable efficiency, Gemma 2 is specifically optimized for rapid inference across a range of hardware platforms. Furthermore, the Gemma family includes diverse models that cater to distinct use cases, ensuring they adapt effectively to user requirements. These lightweight language models feature a decoder and have been trained on an extensive array of textual data, programming code, and mathematical concepts, which enhances their versatility and utility in various applications.

Description

In honor of Archimedes, whose 2311th anniversary we celebrate this year, we are excited to introduce our inaugural Mathstral model, a specialized 7B architecture tailored for mathematical reasoning and scientific exploration. This model features a 32k context window and is released under the Apache 2.0 license. Our intention behind contributing Mathstral to the scientific community is to enhance the pursuit of solving advanced mathematical challenges that necessitate intricate, multi-step logical reasoning. The launch of Mathstral is part of our wider initiative to support academic endeavors, developed in conjunction with Project Numina. Much like Isaac Newton during his era, Mathstral builds upon the foundation laid by Mistral 7B, focusing on STEM disciplines. It demonstrates top-tier reasoning capabilities within its category, achieving remarkable results on various industry-standard benchmarks. Notably, it scores 56.6% on the MATH benchmark and 63.47% on the MMLU benchmark, showcasing the performance differences by subject between Mathstral 7B and its predecessor, Mistral 7B, further emphasizing the advancements made in mathematical modeling. This initiative aims to foster innovation and collaboration within the mathematical community.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

AiAssistWorks Yes 
Hugging Face Yes 
LM-Kit.NET Yes 
Pipeshift Yes 
BlueGPT No 
Clojure Yes 
Fleak No 
Graydient AI No 
Kaggle Yes 
Microsoft Foundry Agent Service No 
Mistral 7B No 
Nebius Token Factory Yes 
Nutanix Enterprise AI No 
OpenLIT No 
PostgresML No 
TensorFlow Yes 
Unify AI No 
Yaseen AI No 
nexos.ai Yes 

Integrations

AiAssistWorks Yes 
Hugging Face Yes 
LM-Kit.NET Yes 
Pipeshift Yes 
BlueGPT Yes 
Clojure No 
Fleak Yes 
Graydient AI Yes 
Kaggle No 
Microsoft Foundry Agent Service Yes 
Mistral 7B Yes 
Nebius Token Factory No 
Nutanix Enterprise AI Yes 
OpenLIT Yes 
PostgresML Yes 
TensorFlow No 
Unify AI Yes 
Yaseen AI Yes 
nexos.ai No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Deployment

Web-Based No 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
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 No 
Live Rep (24/7) Yes 
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 No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Google

Country

United States

Website

ai.google.dev/gemma

Vendor Details

Company Name

Mistral AI

Founded

2023

Country

France

Website

mistral.ai/news/mathstral/

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