DeepScaleR

DeepScaleR

Agentica Project
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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.

About

Level Up Math is an adaptive K-8 math practice platform built for parents who want their child to make real, measurable progress. The platform starts with a brief assessment that pinpoints where each student is across the Common Core math standards, then builds a personalized learning path that adjusts continuously as the student works. Interactive math manipulatives (number lines, place-value blocks, fraction tools, area models, geometric shapes) replace worksheet-style fill-ins, and every problem includes a step-by-step worked solution that explains the underlying reasoning. A parent dashboard shows what the child is working on, where they're stuck, and what comes next. Built as an alternative to drill-and-skill platforms like IXL and gamified-but-shallow products like Prodigy, Level Up Math focuses on real conceptual understanding measured against the actual K-8 curriculum.

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

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

Researchers, students, and developers interested in an AI model capable of mathematical reasoning and logic tasks without requiring heavy hardware

Audience

Parents, K-8 students

Support

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

Support

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

API

Offers API Not Supported

API

Offers API Not Supported

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version Supported
Free Trial Not Supported

Pricing

$15/month
Free Version Not Supported
Free Trial Supported

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

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 Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Supported
In Person Not Supported

Company Information

Agentica Project
Founded: 2025
United States
agentica-project.com

Company Information

Level Up Math
Founded: 2025
United States
levelupmath.com

Alternatives

DeepCoder

DeepCoder

Agentica Project

Alternatives

Phi-4-reasoning

Phi-4-reasoning

Microsoft
Athene-V2

Athene-V2

Nexusflow

Categories

AI Models Supported

Categories

Education Supported

Integrations

No info available.

Integrations

No info available.
Claim DeepScaleR and update features and information
Claim DeepScaleR and update features and information
Claim Level Up Math and update features and information
Claim Level Up Math and update features and information