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Description

DeepCoder, an entirely open-source model for code reasoning and generation, has been developed through a partnership between Agentica Project and Together AI. Leveraging the foundation of DeepSeek-R1-Distilled-Qwen-14B, it has undergone fine-tuning via distributed reinforcement learning, achieving a notable accuracy of 60.6% on LiveCodeBench, which marks an 8% enhancement over its predecessor. This level of performance rivals that of proprietary models like o3-mini (2025-01-031 Low) and o1, all while operating with only 14 billion parameters. The training process spanned 2.5 weeks on 32 H100 GPUs, utilizing a carefully curated dataset of approximately 24,000 coding challenges sourced from validated platforms, including TACO-Verified, PrimeIntellect SYNTHETIC-1, and submissions to LiveCodeBench. Each problem mandated a legitimate solution along with a minimum of five unit tests to guarantee reliability during reinforcement learning training. Furthermore, to effectively manage long-range context, DeepCoder incorporates strategies such as iterative context lengthening and overlong filtering, ensuring it remains adept at handling complex coding tasks. This innovative approach allows DeepCoder to maintain high standards of accuracy and reliability in its code generation capabilities.

Description

Gemini 2.5 Deep Think represents an advanced reasoning capability within the Gemini 2.5 suite, employing innovative reinforcement learning strategies and extended, parallel reasoning to address intricate, multi-faceted challenges in disciplines such as mathematics, programming, scientific inquiry, and strategic decision-making. By generating and assessing various lines of reasoning prior to delivering a response, it yields responses that are not only more detailed and creative but also more accurate, while accommodating longer interactions and integrating tools like code execution and web searches. Its performance has achieved top-tier results on challenging benchmarks, including LiveCodeBench V6 and Humanity’s Last Exam, showcasing significant improvements over earlier iterations in demanding areas. Furthermore, internal assessments reveal enhancements in content safety and tone-objectivity, although there is a noted increase in the model's propensity to reject harmless requests; in light of this, Google is actively conducting frontier safety evaluations and implementing measures to mitigate risks as the model continues to evolve. This ongoing commitment to safety underscores the importance of responsible AI development.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

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

Integrations

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

Pricing Details

Free
Free Trial
Free Version

Pricing Details

No price information available.
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

Google

Founded

1998

Country

United States

Website

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

Product Features

Product Features

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