Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

DeepScaleR is a sophisticated language model comprising 1.5 billion parameters, refined from DeepSeek-R1-Distilled-Qwen-1.5B through the use of distributed reinforcement learning combined with an innovative strategy that incrementally expands its context window from 8,000 to 24,000 tokens during the training process. This model was developed using approximately 40,000 meticulously selected mathematical problems sourced from high-level competition datasets, including AIME (1984–2023), AMC (pre-2023), Omni-MATH, and STILL. Achieving an impressive 43.1% accuracy on the AIME 2024 exam, DeepScaleR demonstrates a significant enhancement of around 14.3 percentage points compared to its base model, and it even outperforms the proprietary O1-Preview model, which is considerably larger. Additionally, it excels on a variety of mathematical benchmarks such as MATH-500, AMC 2023, Minerva Math, and OlympiadBench, indicating that smaller, optimized models fine-tuned with reinforcement learning can rival or surpass the capabilities of larger models in complex reasoning tasks. This advancement underscores the potential of efficient modeling approaches in the realm of mathematical problem-solving.

Description

A versatile JavaScript display engine designed for mathematics, ensuring compatibility across all web browsers. It delivers stunning and accessible mathematical content seamlessly, eliminating any setup requirements for users—MathJax operates effortlessly. This powerful tool enables the conversion of conventional print materials into contemporary, web-friendly formats and ePubs. The dedicated MathJax team offers training sessions for your staff, focusing on how to leverage our resources for developing online educational materials and crafting accessible STEM content. Additionally, MathJax's flexibility allows customization according to your institution's specific needs, including personalized configurations and tailored software workflows. Utilizing CSS with web fonts or SVG instead of bitmap images or Flash, MathJax ensures that equations are scalable alongside surrounding text at any zoom level. Its modular design supports various input formats like MathML, TeX, and ASCIImath, while generating outputs in HTML+CSS, SVG, or MathML. Furthermore, MathJax is compatible with screen readers and enhances user experience through features like expression zoom and interactive exploration, making it an invaluable resource for educators and students alike.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

MarkSnip
MathML Kit

Integrations

MarkSnip
MathML Kit

Pricing Details

Free
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Agentica Project

Founded

2025

Country

United States

Website

agentica-project.com

Vendor Details

Company Name

MathJax

Founded

2009

Country

United States

Website

www.mathjax.org

Product Features

Product Features

Alternatives

Alternatives

Quosera Reviews

Quosera

Sopan Technologies
DeepCoder Reviews

DeepCoder

Agentica Project
Phi-4-reasoning Reviews

Phi-4-reasoning

Microsoft