DeepScaleRAgentica Project
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Related Products
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About
DeepScaleR is a 1.5-billion-parameter language model fine-tuned from DeepSeek-R1-Distilled-Qwen-1.5B using distributed reinforcement learning and a novel iterative context-lengthening strategy that gradually increases its context window from 8K to 24K tokens during training. It was trained on ~40,000 carefully curated mathematical problems drawn from competition-level datasets like AIME (1984–2023), AMC (pre-2023), Omni-MATH, and STILL. DeepScaleR achieves 43.1% accuracy on AIME 2024, a roughly 14.3 percentage point boost over the base model, and surpasses the performance of the proprietary O1-Preview model despite its much smaller size. It also posts strong results on a suite of math benchmarks (e.g., MATH-500, AMC 2023, Minerva Math, OlympiadBench), demonstrating that small, efficient models tuned with RL can match or exceed larger baselines on reasoning tasks.
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About
A JavaScript display engine for mathematics that works in all browsers. Beautiful and accessible math in all browsers No more setup for readers, it just works. MathJax provides tools to transform your content from traditional print sources into modern, accessible web content and ePubs. The MathJax team is available to train your staff in using our resources for preparing online teaching material and creating accessible STEM content. MathJax is highly flexible and can be tailored to the needs of your institution by creating customized configurations and specialized software workflows. MathJax uses CSS with web fonts or SVG, instead of bitmap images or Flash, so equations scale with surrounding text at all zoom levels. MathJax is highly modular on input and output. Use MathML, TeX, and ASCIImath as input and produce HTML+CSS, SVG, or MathML as output. MathJax works with screenreaders & provides expression zoom and interactive exploration.
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Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Not Supported
On-Premises
Supported
iPhone
Not Supported
iPad
Not Supported
Android
Not Supported
Chromebook
Not Supported
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Platforms Supported
Windows
Supported
Mac
Supported
Linux
Supported
Cloud
Supported
On-Premises
Not Supported
iPhone
Supported
iPad
Supported
Android
Supported
Chromebook
Supported
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Audience
Researchers, students, and developers interested in an AI model capable of mathematical reasoning and logic tasks without requiring heavy hardware
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Audience
Researchers, developers and anyone requiring a solution providing a browser engine for mathematics
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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Support
Phone Support
Not Supported
24/7 Live Support
Not Supported
Online
Supported
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API
Offers API
Not Supported
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API
Offers API
Not Supported
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Supported
Free Trial
Not Supported
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Pricing
Free
Free Version
Supported
Free Trial
Not Supported
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Reviews/
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Reviews/
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Training
Documentation
Supported
Webinars
Not Supported
Live Online
Not Supported
In Person
Not Supported
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Company InformationAgentica Project
Founded: 2025
United States
agentica-project.com
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Company InformationMathJax
Founded: 2009
United States
www.mathjax.org
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Alternatives |
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Categories |
Categories |
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Integrations
Eurekos
Not Supported
MarkSnip
Not Supported
MathML Kit
Not Supported
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