Introduction
Today, large language models (LLMs) play a crucial role. In early 2025, as the competition for AI intensified, Alibaba launched the new Qwen2.5-max AI model, and DeepSeek, a company from Hangzhou, China, launched the R1 model, which represents the pinnacle of LLM technology.
Deepseek R1 is an open source AI model that has attracted worldwide attention for its excellent user experience and performance. It also brings more hope for the application scenarios and future of AI. An open source model means that any individual or company with sufficient hardware conditions can try to deploy Deepseek R1 locally and experience AI functions similar to those of open ai o1.
This article will focus on Qwen2.5-max, analyze its features in depth, compare it with DeepSeek R1, explain the differences between the two and their application scenarios, and finally provide an experience address to help you choose the most suitable model.
Qwen2.5-max model introduction
Qwen series is a famous LLM product, Qwen2.5-max, the latest AI large model product in the Alibaba Cloud Qwen series, is positioned as a large-scale MoE (Mixture-of-Experts) model, aiming to reach new heights of model intelligence. It hopes to achieve better performance and meet more needs and application scenarios. It has some core advantages:
Massive data pre-training: Qwen2.5-max is empowered by a giant dataset of 20 trillion tokens, which gives it strong language comprehension and a vast knowledge base. if we want to get a perfect AI LLM, a good data is important.
Excellent reasoning ability: Reasoning is Qwen2.5-max’s trump card! It has demonstrated extraordinary strength in the rigorous tests of authoritative benchmarks such as MMLU-Pro, LiveCodeBench, LiveBench, and Arena-Hard, this score was proving that it good at complex logic, knowledge questions, and problem solving.
Multilingual seamless switching: Multilingual processing is another highlight of Qwen2.5-max, especially in the field of non-English NLP, where its advantages significantly surpass those of DeepSeek R1. Building a global application? Qwen2.5-max is the ideal choice for you.
Knowledge-based AI first choice: Building knowledge-intensive applications? Qwen2.5-max is the right choice for you! Its powerful knowledge base and reasoning capabilities provide a solid foundation for knowledge mapping, intelligent Q&A, content creation and other application scenarios.
Multimodal capabilities expanded: Equipped with image generation skills, Qwen2.5-max can easily handle multimodal data such as text, images, and videos, unlocking richer application possibilities.
Qwen2.5-max vs DeepSeek R1: Comparison
Qwen2.5-max and DeepSeek R1 are both leaders in LLM, but each has its own focus and distinctive features:
| Features/Models | Qwen2.5-max | DeepSeek R1 |
| Model Architecture | Large-scale MoE model | MoE model (671 billion parameters, 37 billion activations) |
| Training Data Scale | 20 trillion tokens | Not mentioned explicitly, based on DeepSeek-V3-Base Training |
| Core Advantages | Inference, multilingual processing, knowledge-based AI | coding capabilities, question answering, web search integration |
| Multi-modal capabilities | Image generation | Image analysis, Web search |
| Open source | Qwen series usually have open source versions, but the open source version of 2.5-max is to be confirmed. | Open source models are more flexible. |
| hardware requirements | Higher | Lower |
| Applicable scenarios | Focus on complex reasoning, multilingual applications, knowledge-intensive tasks, multimodal generation | encoding tasks, question answering systems, applications that require the integration of web information, and hardware-constrained scenarios. |
| Benchmark test advantages | Multilingual processing, XTREME | question answering (according to some sources) |
One sentence to summarize:
Choose Qwen2.5-max: reasoning, multilingual, knowledge-intensive, multimodal generation? Choose it!
Choose DeepSeek R1: coding, question answering, web integration, hardware-constrained? Choose it!
Experience address: sneak preview
Qwen2.5-max:
The official experience address is still being updated, so please pay close attention:
Qwen online experience address
API experience address
DeepSeek R1:
Warm reminder: The experience address may change, please refer to the latest official information.
Summary: Choose the model that suits you best
Qwen2.5-max and DeepSeek R1, the LLM field’s twin stars, each with their own strengths. Depending on your application scenario and core needs, choosing the most suitable model is the way to go. We look forward to continued breakthroughs in AI technology, which will bring unlimited possibilities to mankind!
