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What is Gemini 2.5 Deep Think?

Gemini 2.5 Deep Think showcases advanced reasoning abilities within the Gemini 2.5 framework, utilizing cutting-edge reinforcement learning techniques and extensive parallel reasoning to tackle complex, multifaceted problems across various fields such as mathematics, programming, scientific research, and strategic planning. By exploring and evaluating multiple reasoning pathways before arriving at a conclusion, it produces responses that are not only intricate and inventive but also highly accurate, supporting extensive interactions and incorporating tools like code execution and web searches. Its performance has consistently achieved exceptional results on rigorous benchmarks, including LiveCodeBench V6 and Humanity’s Last Exam, indicating substantial progress compared to previous versions in challenging domains. Additionally, internal evaluations have indicated improvements in both content safety and maintaining an objective tone; however, there has been a noticeable rise in the model's tendency to deny innocuous requests. In response to this, Google is actively pursuing frontier safety assessments and enacting strategies to reduce associated risks as the model advances. This proactive approach to safety highlights the critical need for responsible development in the realm of artificial intelligence. As the technology evolves, ongoing refinements will likely enhance its capabilities and ensure that it remains aligned with ethical standards and user expectations.

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

Media

Integrations Supported

CodeMender
Gemini
Gemini 2.5 Flash
Gemini 2.5 Pro
Gemini 3 Deep Think
Gemini Enterprise
Google AI Ultra

Integrations Supported

CodeMender
Gemini
Gemini 2.5 Flash
Gemini 2.5 Pro
Gemini 3 Deep Think
Gemini Enterprise
Google AI Ultra

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
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

Google

Date Founded

1998

Company Location

United States

Company Website

blog.google/products/gemini/gemini-2-5-deep-think/

Company Facts

Organization Name

Agentica Project

Date Founded

2025

Company Location

United States

Company Website

agentica-project.com

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Categories and Features

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