Mathstral

Mathstral

Mistral 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

MiniMax M3.1 Flash is a hosted large language model for developers building coding assistants, AI agents, and software applications. Available through MiniMax’s API and MiniMax Code, it accepts text, image, and video input and generates text responses. Documented uses include code generation and debugging, multi-step reasoning, tool use, codebase and document analysis, and computer-use workflows. The API offers a context window of up to 1 million tokens, adjustable reasoning effort, and OpenAI-compatible and Anthropic-compatible request formats. Usage is billed by input, output, and cached-input tokens. MiniMax provides documentation for API integration and model use. M3.1 Flash is available through the hosted API, M Plan, and MiniMax Code; model weights are planned for a later release.

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 Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

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

Audience

Software developers and organizations building coding assistants, AI agents, and applications that use a hosted language model.

Support

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

Support

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

API

Offers API Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Open source
Free Version Supported
Free Trial Not Supported

Pricing

$0.15/1M input tokens
Input: $0.15 per 1 million tokens; output: $0.60 per 1 million tokens; cached input: $0.015 per 1 million tokens. Standard pay-as-you-go billing in USD, based on token usage.
Free Version Not 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

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Reviews/Ratings

Overall 5.0 / 5
ease 5.0 / 5

Pros & Cons from Real Users

Pros

  • It feels noticeably faster than M3 while still being strong enough for coding, research, computer-use tasks, and longer agent workflows. The 1M-token context window is a big advantage too. I can keep large repos, long documents, screenshots, video context, and a lot of prior agent history in the same session without constantly trimming things down. The pricing is probably the best part. At $0.15 per million input tokens and $0.60 per million output tokens, I can run it heavily without worrying that every agent loop is getting expensive. I also like how much MiniMax improved the agent side. M3.1 Flash is aimed at real multi-step work across coding, enterprise automation, computer use, and even cybersecurity, rather than just fast chat responses.

Cons

  • The main downside is that reasoning is always enabled, so it is not quite as lightweight as a pure instant-response model for trivial tasks.

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

Company Information

MiniMax
Founded: 2022
China
www.minimax.io/blog/minimax-m31f

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Categories

AI Models Supported
Foundation Models Supported

Categories

AI Coding Models Supported
AI Models Supported
Foundation Models Supported
Multimodal Models Supported

Integrations

302.AI Supported
Airtrain Supported
Amazon Bedrock Supported
Arize Phoenix Supported
Codestral Mamba Supported
Fireworks AI Not Supported
Fleak Supported
Hermes Agent Not Supported
Mammouth AI Supported
Melies Supported
MiniMax Code Not Supported
MiniMax Mavis Not Supported
Mistral 7B Supported
Mixtral 8x22B Supported
Mixtral 8x7B Supported
NexalAI Supported
Overseer AI Supported
Roo Code Not Supported
Symflower Supported
Verta Supported

Integrations

302.AI Not Supported
Airtrain Not Supported
Amazon Bedrock Not Supported
Arize Phoenix Not Supported
Codestral Mamba Not Supported
Fireworks AI Supported
Fleak Not Supported
Hermes Agent Supported
Mammouth AI Not Supported
Melies Not Supported
MiniMax Code Supported
MiniMax Mavis Supported
Mistral 7B Not Supported
Mixtral 8x22B Not Supported
Mixtral 8x7B Not Supported
NexalAI Not Supported
Overseer AI Not Supported
Roo Code Supported
Symflower Not Supported
Verta Not Supported
Claim Mathstral and update features and information
Claim Mathstral and update features and information
Claim MiniMax M3.1 Flash and update features and information
Claim MiniMax M3.1 Flash and update features and information