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Description
This math homework application offers precise, immediate, and comprehensive solutions for math problems at any level. It excels at addressing difficult word problems and tackling the most intricate mathematical inquiries. If you continue to face challenges with your math assignments, you can consult with CameraMath's carefully selected, top-tier math tutors who are available online around the clock. As a leading platform for math problem-solving and learning, CameraMath serves millions of students seeking answers, preparing for exams, and exploring mathematical concepts. The app delivers not only a thorough solution but also a clear explanation for every math query, guiding you through each step in a way that enhances your understanding of how to reach the answer. CameraMath exposes learners to a variety of problem-solving techniques, fostering a deep and adaptable knowledge of mathematics. You can discover multiple methods for resolving even the most daunting math challenges. Word problems often pose a significant obstacle in math homework, and while many math solvers may struggle with them, CameraMath consistently rises to the occasion, ensuring you can tackle every problem with confidence. With its user-friendly interface and expert assistance, CameraMath is designed to empower students in their pursuit of math mastery.
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.
API Access
Has API
API Access
Has API
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
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
CameraMath
Website
cameramath.com
Vendor Details
Company Name
Agentica Project
Founded
2025
Country
United States
Website
agentica-project.com