Mathstral

Mathstral

Mistral AI
Pokee-Isaac

Pokee-Isaac

Pokee AI
+
+

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About

As a tribute to Archimedes, whose 2311th anniversary we’re celebrating this year, we are proud to release our first Mathstral model, a specific 7B model designed for math reasoning and scientific discovery. The model has a 32k context window published under the Apache 2.0 license. We’re contributing Mathstral to the science community to bolster efforts in advanced mathematical problems requiring complex, multi-step logical reasoning. The Mathstral release is part of our broader effort to support academic projects, it was produced in the context of our collaboration with Project Numina. Akin to Isaac Newton in his time, Mathstral stands on the shoulders of Mistral 7B and specializes in STEM subjects. It achieves state-of-the-art reasoning capacities in its size category across various industry-standard benchmarks. In particular, it achieves 56.6% on MATH and 63.47% on MMLU, with the following MMLU performance difference by subject between Mathstral 7B and Mistral 7B.

About

Pokee-Isaac text-only agentic model with a usable context window of up to 10 million tokens. It is designed to reason, plan, call tools, and execute long-horizon tasks while remaining small enough to deploy inside a VPC, on customer premises, on a workstation, or on-device. Pokee reports that Isaac maintains strong long-context performance across RULER from 256K through 10M tokens and leads the evaluated panel on multi-needle retrieval at 256K, 512K, and 1M. Its agentic architecture is built for deterministic function calling, sustained multi-turn coherence, real-shell execution, and discovering and composing tools across live MCP servers. In Pokee’s controlled benchmarks, Isaac ranked first on BFCL v4 and τ³-bench, second on the Terminal-Bench 2.1 text-only subset, and third on MCP-Atlas. Security testing with DTAP also showed the lowest combined attack success rate in the comparison panel while retaining strong benign-task performance.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Individuals focused on mathematical research looking for an AI tool to enhance their problem-solving capabilities

Audience

AI infrastructure teams that need long-context, tool-using models they can deploy privately across cloud, on-premises, workstation, or edge hardware

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Open source
Free Version
Free Trial

Pricing

$0.15 per 1M tokens
Free Version
Free Trial

Reviews/Ratings

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

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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
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Mistral AI
Founded: 2023
France
mistral.ai/news/mathstral/

Company Information

Pokee AI
Founded: 2024
United States
console.pokee.ai/model

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Categories

Categories

Integrations

AiAssistWorks
AlphaCorp
AnythingLLM
Codestral Mamba
Diaflow
Echo AI
GMTech
Hugging Face
HumanLayer
Ministral 3B
Mistral 7B
Mixtral 8x7B
Numina
Respan
SydeLabs
Toolmark
Tune AI
Wordware
bolt.diy

Integrations

AiAssistWorks
AlphaCorp
AnythingLLM
Codestral Mamba
Diaflow
Echo AI
GMTech
Hugging Face
HumanLayer
Ministral 3B
Mistral 7B
Mixtral 8x7B
Numina
Respan
SydeLabs
Toolmark
Tune AI
Wordware
bolt.diy
Claim Mathstral and update features and information
Claim Mathstral and update features and information
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Claim Pokee-Isaac and update features and information