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Description

DeepSeek-V3.2 is a highly optimized large language model engineered to balance top-tier reasoning performance with significant computational efficiency. It builds on DeepSeek's innovations by introducing DeepSeek Sparse Attention (DSA), a custom attention algorithm that reduces complexity and excels in long-context environments. The model is trained using a sophisticated reinforcement learning approach that scales post-training compute, enabling it to perform on par with GPT-5 and match the reasoning skill of Gemini-3.0-Pro. Its Speciale variant overachieves in demanding reasoning benchmarks and does not include tool-calling capabilities, making it ideal for deep problem-solving tasks. DeepSeek-V3.2 is also trained using an agentic synthesis pipeline that creates high-quality, multi-step interactive data to improve decision-making, compliance, and tool-integration skills. It introduces a new chat template design featuring explicit thinking sections, improved tool-calling syntax, and a dedicated developer role used strictly for search-agent workflows. Users can encode messages using provided Python utilities that convert OpenAI-style chat messages into the expected DeepSeek format. Fully open-source under the MIT license, DeepSeek-V3.2 is a flexible, cutting-edge model for researchers, developers, and enterprise AI teams.

Description

Language plays a crucial role in showcasing and enhancing understanding, which is essential to the human experience. It empowers individuals to share thoughts, convey ideas, create lasting memories, and foster empathy and connection with others. These elements are vital for social intelligence, which is why our teams at DeepMind focus on various facets of language processing and communication in both artificial intelligences and humans. Within the larger framework of AI research, we are convinced that advancing the capabilities of language models—systems designed to predict and generate text—holds immense promise for the creation of sophisticated AI systems. Such systems can be employed effectively and safely to condense information, offer expert insights, and execute commands through natural language. However, the journey toward developing beneficial language models necessitates thorough exploration of their possible consequences, including the challenges and risks they may introduce into society. By understanding these dynamics, we can work towards harnessing their power while minimizing any potential downsides.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

BERT No 
ChatGPT No 
Constellation Gate AI Yes 
DeepSeek Yes 
Dolly No 
GPT-4 No 
Hugging Face Yes 
Llama No 
Llama 2 No 
Llama 3.2 No 
Llama 3.3 No 
Lorka Yes 
Ollama Yes 
OpenTag Yes 
Oxlo.ai Yes 
Shiori Yes 
Stable LM No 
WeatherNext No 
Zo Computer Yes 

Integrations

BERT Yes 
ChatGPT Yes 
Constellation Gate AI No 
DeepSeek No 
Dolly Yes 
GPT-4 Yes 
Hugging Face No 
Llama Yes 
Llama 2 Yes 
Llama 3.2 Yes 
Llama 3.3 Yes 
Lorka No 
Ollama No 
OpenTag No 
Oxlo.ai No 
Shiori No 
Stable LM Yes 
WeatherNext Yes 
Zo Computer No 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs No 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

DeepSeek

Founded

2023

Country

China

Website

deepseek.com

Vendor Details

Company Name

Google DeepMind

Country

United States

Website

www.deepmind.com/blog/language-modelling-at-scale-gopher-ethical-considerations-and-retrieval

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