Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total
ease
features
design
support

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • ONLYOFFICE Docs Reviews & Ratings
    708 Ratings
    Company Website
  • Ango Hub Reviews & Ratings
    15 Ratings
    Company Website
  • Vertex AI Reviews & Ratings
    944 Ratings
    Company Website
  • Google AI Studio Reviews & Ratings
    11 Ratings
    Company Website
  • LM-Kit.NET Reviews & Ratings
    25 Ratings
    Company Website
  • AthenaHQ Reviews & Ratings
    33 Ratings
    Company Website
  • Pipedrive Reviews & Ratings
    10,133 Ratings
    Company Website
  • Evertune Reviews & Ratings
    1 Rating
    Company Website
  • OpenMetal Reviews & Ratings
    39 Ratings
    Company Website
  • imgproxy Reviews & Ratings
    15 Ratings
    Company Website

What is Open R1?

Open R1 is a community-driven, open-source project aimed at replicating the advanced AI capabilities of DeepSeek-R1 through transparent and accessible methodologies. Participants can delve into the Open R1 AI model or engage in a complimentary online conversation with DeepSeek R1 through the Open R1 platform. This project provides a meticulous implementation of DeepSeek-R1's reasoning-optimized training framework, including tools for GRPO training, SFT fine-tuning, and synthetic data generation, all released under the MIT license. While the foundational training dataset remains proprietary, Open R1 empowers users with an extensive array of resources to build and refine their own AI models, fostering increased customization and exploration within the realm of artificial intelligence. Furthermore, this collaborative environment encourages innovation and shared knowledge, paving the way for advancements in AI technology.

What is DeepScaleR?

DeepScaleR is an advanced language model featuring 1.5 billion parameters, developed from DeepSeek-R1-Distilled-Qwen-1.5B through a unique blend of distributed reinforcement learning and a novel technique that gradually increases its context window from 8,000 to 24,000 tokens throughout training. The model was constructed using around 40,000 carefully curated mathematical problems taken from prestigious competition datasets, such as AIME (1984–2023), AMC (pre-2023), Omni-MATH, and STILL. With an impressive accuracy rate of 43.1% on the AIME 2024 exam, DeepScaleR exhibits a remarkable improvement of approximately 14.3 percentage points over its base version, surpassing even the significantly larger proprietary O1-Preview model. Furthermore, its outstanding performance on various mathematical benchmarks, including MATH-500, AMC 2023, Minerva Math, and OlympiadBench, illustrates that smaller, finely-tuned models enhanced by reinforcement learning can compete with or exceed the performance of larger counterparts in complex reasoning challenges. This breakthrough highlights the promising potential of streamlined modeling techniques in advancing mathematical problem-solving capabilities, encouraging further exploration in the field. Moreover, it opens doors for developing more efficient models that can tackle increasingly challenging problems with great efficacy.

Media

No images available

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Free
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Open R1

Date Founded

2025

Company Location

United Kingdom

Company Website

open-r1.com

Company Facts

Organization Name

Agentica Project

Date Founded

2025

Company Location

United States

Company Website

agentica-project.com

Categories and Features

Categories and Features

Popular Alternatives

Phi-4-reasoning Reviews & Ratings

Phi-4-reasoning

Microsoft

Popular Alternatives

DeepCoder Reviews & Ratings

DeepCoder

Agentica Project
DeepSeek R1 Reviews & Ratings

DeepSeek R1

DeepSeek
Phi-4-reasoning Reviews & Ratings

Phi-4-reasoning

Microsoft
DeepScaleR Reviews & Ratings

DeepScaleR

Agentica Project