
What is Qwen2.5-Max?
Qwen2.5-Max is an AliCloudlit. ten thousand questions on general principles (idiom); fig. a long list of questions and answersThe team officially released the flagship version on January 29, 2025Large Model. The model is based on an advanced MoE (Mixture of Experts) architecture and uses massive data of over 20 trillion tokens for pre-training, with excellent language processing capabilities and programming assistance.
Qwen2.5-Max performs well in a number of authoritative benchmarks, comprehensively outperforming a number of industry-leading models including DeepSeek V3, GPT-4o and Claude-3.5. AliCloud adopted an open source strategy to release Qwen2.5-Max, aiming to promote the openness, sharing and development of AI technology. This initiative enables developers to innovate based on the model, driving the prosperity of the entire technology ecosystem.
The release of Qwen2.5-Max marks another important breakthrough in China's AI technology in the high-performance and low-cost technology route.
DEMO Experience Address:https://www.modelscope.cn/studios/Qwen/Qwen2.5-Max-Demo
Qwen2.5-Max Technical Features
- Hyperscale and Massive Data: Qwen2.5-Max uses massive data of more than 20 trillion tokens in the pre-training phase, which covers a variety of textual resources on the Internet such as news reports, academic papers, novels, blogs, forum posts, and so on, covering almost all areas of human knowledge and providing a rich knowledge base for the model.
- Advanced MoE ArchitectureQwen2.5-Max is built on the advanced MoE architecture, which realizes the optimal allocation of computing resources by intelligently selecting appropriate "expert" models to handle different tasks, effectively improving the speed and efficiency of reasoning.
- Optimization techniques: Qwen2.5-Max has been optimized with supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) techniques to further improve the model's performance in terms of knowledge, programming, general competence, and human alignment.
Qwen2.5-Max Performance
- Global Ranking: On Chatbot Arena, which is recognized as the most fair and authoritative performance testing platform for large models in the industry, Qwen 2.5-Max was ranked seventh globally with 1,332 points, making it the Chinese large model champion in the non-reasoning category.
- Individual competencies: Qwen2.5-Max ranked first in individual competencies such as Math and Programming, and second in Hard prompts (Hard prompts). In mainstream benchmarks such as Arena-Hard, LiveBench, LiveCodeBench, GPQA-Diamond and MMLU-Pro, Qwen2.5-Max outperforms Claude-3.5-Sonnet and almost completely outperforms GPT-4o, DeepSeek-V3 and Llama- 3.1-405B.
Qwen2.5-Max Application Scenarios and Functions
- Long Text Processing: Qwen 2.5-Max supports context lengths of up to 128K and generates up to 8K of content, making it capable of handling long text and complex tasks such as long-form report generation.
- Multimodal processing capability: Qwen2.5-Max is equipped with visual comprehension capabilities and can process images and video content, showing a broad application prospect.
- Programming Aids: Qwen 2.5-Max excels in math and programming, with powerful programming aids to help developers increase programming efficiency.
Qwen2.5-Max Usage and Compatibility
- Usage: Enterprises can call the API service of Qwen2.5-Max models in AliCloud Hundred Refinement, and developers can also experience the latest models for free in the Qwen Chat platform.
- compatibility: Qwen2.5-Max's API is obtained through AliCloud and is compatible with OpenAI-API, making it easy for developers to integrate and use.
data statistics
Relevant Navigation

Based on industrial data and technology, Jingdong has developed an intelligent large model with extensive industry application capabilities, and is committed to providing efficient and intelligent solutions for enterprises.

Kling LM
Racer's self-developed advanced video generation model supports the generation of high-quality videos based on text descriptions, helping users to efficiently create artistic video content.

Moonshot
(Moonshot AI) launched a large-scale AI general model with hundreds of millions of parameters, capable of processing inputs of up to 200,000 Chinese characters, and widely used in natural language processing, intelligent recommendation, medical diagnosis and other fields, demonstrating excellent generalization ability and accuracy.

HunyuanImage2.1
Tencent launched the open source raw image model, which natively supports 2K HD raw images, accurately parses complex semantics, and can efficiently generate high-quality images with Chinese and English fusion.

GWM-1
Runway's first universal world model simulates physical laws and dynamic environments through frame-by-frame pixel prediction technology. It supports robot training, digital human generation, and cross-domain simulation, redefining how AI understands and interacts with the world.

Claude 3.7 Sonnet
Anthropic has released the world's first hybrid reasoning model that demonstrates superior performance and flexibility by being able to flexibly switch between rapid response and deeper reflection based on different needs.

Xiaomi MiMo
Xiaomi's open-sourced 7 billion parameter inference macromodel, which outperforms models such as OpenAI o1-mini in mathematical reasoning and code competitions by a small margin.

ERNIE
Baidu's industrial-grade knowledge-enhancing big models, with industry-leading natural language understanding and generation capabilities, are widely used in all kinds of natural language processing and generation tasks, helping enterprises realize intelligent upgrading.
No comments...
