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What is QVQ-Max?

QVQ-Max is a cutting-edge visual reasoning AI that merges detailed observation with sophisticated reasoning to understand and analyze images, videos, and diagrams. This AI can identify objects, read textual labels, and interpret visual data for solving complex math problems or predicting future events in videos. Furthermore, it excels at flexible applications, such as designing illustrations, creating video scripts, and enhancing creative projects. It also assists users in educational contexts by helping with math and physics problems that involve diagrams, offering intuitive explanations of challenging concepts. In daily life, QVQ-Max can guide decision-making, such as suggesting outfits based on wardrobe photos or providing step-by-step cooking advice. As the platform develops, its ability to handle even more complex tasks, like operating devices or playing games, will expand, making it an increasingly valuable tool in various aspects of life and work.

What is DeepSeek-V3.2-Speciale?

DeepSeek-V3.2-Speciale represents the pinnacle of DeepSeek’s open-source reasoning models, engineered to deliver elite performance on complex analytical tasks. It introduces DeepSeek Sparse Attention (DSA), a highly efficient long-context attention design that reduces the computational burden while maintaining deep comprehension and logical consistency. The model is trained with an expanded reinforcement learning framework capable of leveraging massive post-training compute, enabling performance not only comparable to GPT-5 but demonstrably surpassing it in internal tests. Its reasoning capabilities have been validated through gold-winning solutions across major global competitions, including IMO 2025 and IOI 2025, with official submissions released for transparency and peer assessment. DeepSeek-V3.2-Speciale is intentionally designed without tool-calling features, focusing every parameter on pure reasoning, multi-step logic, and structured problem solving. It introduces a reworked chat template featuring explicit thought-delimited sections and a structured message format optimized for agentic-style reasoning workflows. The repository includes Python-based utilities for encoding and parsing messages, illustrating how to format prompts correctly for the model. Supporting multiple tensor types (BF16, FP32, FP8_E4M3), it is built for both research experimentation and high-performance local deployment. Users are encouraged to use temperature = 1.0 and top_p = 0.95 for best results when running the model locally. With its open MIT license and transparent development process, DeepSeek-V3.2-Speciale stands as a breakthrough option for anyone requiring industry-leading reasoning capacity in an open LLM.

Media

Media

Integrations Supported

Integrations Supported

DeepSeek
Hugging Face

API Availability

API Availability

Pricing Information

Free
Open source
Free Version

Pricing Information

Free
Open source
Free Version

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Customer Service / Support

Not specified

Customer Service / Support

Not specified

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Alibaba

Date Founded

1999

Company Location

China

Company Website

qwenlm.github.io/blog/qvq-max-preview/

Company Facts

Organization Name

DeepSeek

Date Founded

2023

Company Location

China

Company Website

deepseek.com

Categories and Features

AI Models

Not specified

AI Vision Models

Not specified

Categories and Features

AI Models

Not specified

AI Reasoning Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

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