The AI race isn’t just between the US and China anymore. China is competing with itself while the US is pouring in billions to stay ahead. Alibaba just dropped Qwen 2.5 Max, claiming it beats open as GPT 4.0, Deepseeks V3, and even Meta’s latest LLMs model.
Meanwhile, ByteDance and DeepSeek are making big moves, forcing OpenAI, Perplexity, and Anthropic to fight back with massive funding, and now SoftBank is in talks to invest $25 billion in OpenAI, a deal that would make it open AI’s biggest backer ever.
So who’s actually leading the AI Revolution? Let’s break it down.
Introduction to QWEN 2.5 Max
What is QWEN 2.5 Max?
QWEN 2.5 Max is an advanced large language model (LLM) developed by Alibaba Cloud as part of their Tongyi Qianwen AI model series.
Alibaba just launched Qwen 2.5 Max, and the message is clear: Deep’s dominance won’t go unchallenged. The Lunar New Year surprise launch shows Alibaba’s feeling the heat, the company says.
When Qwen 2.5 Max outperforms OpenAI’s GPT-4 and even DeepSeek’s V3, it’s a bold claim in an AI race that’s moving at lightning speed, but Alibaba isn’t the only one reacting.
Just 2 days after DeepSeek released its R1 model and ByteDance upgraded its AI, claiming it beats OpenAI in key performance benchmarks.
Also read – Did DeepSeek burst the AI bubble? Big Tech in panic mode
Is Qwen AI free?
Yes, Qwen AI allows free access through multiple consumerisms. Qwen AI, developed by Alibaba Cloud, offers many open-source models suitable for natural language processing, code assistance, etc. One of the most famous platforms is Qwen Chat: Qwen Chat Web Interface, an easy-to-handle web interface through which developers and researchers can effortlessly touch and play with the capabilities of Qwen AI for free.
What is Qwen 2.5 32b int8 gguf ?
Qwen2.5-32B-Instruct-GGUF is a quantized version of Alibaba Cloud’s Qwen2.5-32B-Int8 model, designed to enhance efficiency and reduce resource requirements. The GGUF format is optimized for performance, making it suitable for various hardware configurations.
Models Alibaba Cloud’s Qwen AI series
Alibaba Cloud’s Qwen AI series encompasses a variety of models tailored for different applications:
- Qwen 7B: Introduced in April 2023, this model marked the beginning of Alibaba’s open-source journey in large language models. qwenlm.github.io
- Qwen 2: Released in June 2024, this version includes models with parameter sizes of 0.5B, 1.5B, 7B, 14B, and 72B, offering significant improvements in coding, mathematics, and multilingual capabilities across 29 languages. qwen2.org
- Qwen 2.5: Launched in September 2024, this update introduced advanced features and optimizations, enhancing the model’s performance in various tasks. qwenlm.github.io
- Qwen 2.5-Max: Unveiled in January 2025, this is Alibaba’s latest and most powerful model, claiming to outperform other leading models like GPT-4o, DeepSeek-V3, and Llama-3.1-405B in key benchmarks.
What is Qwen Hugging Face?
Qwen Hugging Face refers to the integration of the Qwen series of large language models with Hugging Face’s ecosystem , which is one of the most popular open-source platforms for natural language processing (NLP) and machine learning models. This collaboration allows users to access, fine-tune, and deploy Qwen models through Hugging Face’s tools and infrastructure.
China is now home to three top AI contenders.
DeepSeek: The Breakout Startup Shaping Up Global AI Alibaba squinched the big tech answer to the AI disruption by leveraging TikTok data to train the next-gen AI model. Now let’s break down the three-way battle between Deep Seek OpenAI and Alibaba.
Also read– DeepSeek R1 blog: This Free AI Model is Mind-Blowing
QWEN 2.5 max Vs. Deepseek R1 VS OpenAI
| Feature/Task | DeepSeek R1 (Full Model) | Alibaba Qwen 2.5 Max | ChatGPT (o1) | DeepSeek R1 (14B) | ChatGPT (o3-mini) |
|---|---|---|---|---|---|
| Problem Solving | B – Slow, identified key issues but lacked depth | A – Fast, identified more issues including event delegation | B – Faster than DeepSeek, but shallow response | C – Quick but missed some CSS issues | B – Identified main issues but nothing extra |
| Coding – Custom Cursor | C – Slow (58s), created functional code but did not fully replace cursor | A – Fastest response, functional code but not very advanced | A+ – Best solution, used SVG for a proper cursor replacement | F – Failed to change cursor, only highlighted background | B – Created a working cursor but only as a square |
| Web Design Analysis | B – Identified key mistakes but lacked specific recommendations | Not supported | A – Best performance, identified specific issues with layout and content | F – Generic feedback, no real analysis | Not supported |
| Overall Performance | A: Best all-around performance | B – Great for coding, fast responses, but lacks image support | A – Best all-around performance | E – Underperformed significantly | B – Balanced but not the best |
Introduction
DeepSeek R1 is currently one of the most popular AI models, topping the App Store charts. In this blog, we compare it against other leading AI models, including Qwen 2.5 Max, ChatGPT o1, and o3-mini, in programming, web design, and problem-solving. We assess their performance based on multiple coding and design challenges to see which model excels in different tasks.
Setting Up the Test Environment
To conduct a fair comparison, we set up each model in controlled environments:
- DeepSeek R1 (Full Model) running on its official platform.
- Qwen 2.5 Max (Alibaba) tested online.
- ChatGPT o1 and o3-mini (OpenAI) tested via their respective platforms.
- DeepSeek R1 (14B) set up on a local Docker container using Open Web UI.
Additionally, a testing website was built using Wick Studio to evaluate the coding outputs of each model.
Challenge 1: Problem-Solving in JavaScript & CSS
For the first test, a JavaScript and CSS code snippet was intentionally modified with errors. Each AI model was tasked with identifying and fixing these errors without any hints or guidance.
Results:
- DeepSeek R1 (Full Model): Took 21 seconds to analyze and fix basic errors, like a misspelled menu and incorrect CSS units. However, it did not identify deeper issues.
- Qwen 2.5 Max: Fastest response, found all key errors, and even identified hidden issues like an event delegation problem and a visibility issue in the dropdown menu. Best response.
- ChatGPT o1: Took 12 seconds, identified main issues but did not provide deeper analysis.
- DeepSeek R1 (14B): Faster but missed a key CSS issue that other models caught.
- ChatGPT o3-mini: Took 17 seconds, identified basic mistakes but lacked advanced analysis.
Problem-Solving Scores:
| Model | Score | Remarks |
|---|---|---|
| Qwen 2.5 Max | A | Fast, detailed response, best analysis |
| DeepSeek R1 (Full) | B | Slow, identified only key errors |
| ChatGPT o1 | B | Faster than DeepSeek but still shallow |
| DeepSeek R1 (14B) | C | Missed key CSS mistakes |
| ChatGPT o3-mini | B | Basic fixes, no in-depth analysis |
Challenge 2: Coding a Custom Mouse Cursor
Each model was given a prompt to generate a 50×50 pixel teal cursor that follows the mouse when hovering over hyperlinks.
Results:
- DeepSeek R1 (Full Model): Took 58 seconds, created JavaScript and CSS code, but failed to completely replace the cursor, causing an overlap issue.
- Qwen 2.5 Max: Generated the code quickly and performed the task as requested, but lacked complexity.
- ChatGPT o1: Best solution – used an SVG-based cursor replacement, making it more advanced than others.
- DeepSeek R1 (14B): Failed – only highlighted the hyperlink instead of changing the cursor.
- ChatGPT o3-mini: Created a functional cursor, but it was just a square, not a fully customized design.
Coding Scores:
| Model | Score | Remarks |
|---|---|---|
| ChatGPT o1 | A+ | Best approach, used SVG for a proper cursor |
| Qwen 2.5 Max | A | Fastest, but less advanced |
| DeepSeek R1 (Full) | C | Overlapped cursor issue |
| DeepSeek R1 (14B) | F | Completely failed task |
| ChatGPT o3-mini | B | Created a square cursor, but not ideal |
Challenge 3: Web Design Analysis
To test web design capabilities, an image of a webpage with intentional design flaws was uploaded. Each model was asked to analyze and suggest improvements.
Results:
- DeepSeek R1 (Full Model): Took 24 seconds, identified poor visual hierarchy, spacing, and font issues but lacked specific recommendations.
- Qwen 2.5 Max: Not supported (cannot analyze images).
- ChatGPT o1: Best response, provided detailed feedback on layout issues, color choices, and spacing.
- DeepSeek R1 (14B): Failed—gave generic design principles rather than analyzing the actual image.
- ChatGPT o3-mini: Not supported (cannot analyze images).
Web Design Scores:
| Model | Score | Remarks |
|---|---|---|
| ChatGPT o1 | A | Best performance, detailed recommendations |
| DeepSeek R1 (Full) | B | Decent, but lacked specificity |
| Qwen 2.5 Max | N/A | No image analysis support |
| DeepSeek R1 (14B) | F | Generic feedback, no real analysis |
| ChatGPT o3-mini | N/A | No image analysis support |
Final Scores and Ranking
Based on the performance across problem-solving, coding, and web design tasks, here’s the final ranking:
| Model | Final Score | Remarks |
|---|---|---|
| ChatGPT o1 | A | Best overall performance across all tasks |
| Qwen 2.5 Max | B | Best for coding, but lacks image support |
| DeepSeek R1 (Full) | B | Good, but slow and lacked depth |
| ChatGPT o3-mini | B | Balanced but not the best |
| DeepSeek R1 (14B) | E | Underperformed in all tests |
Conclusion
From this comparison, ChatGPT o1 emerged as the best all-around performer, excelling in both coding and web design tasks. Qwen 2.5 Max performed exceptionally well in coding but lacked image processing capabilities. DeepSeek R1 showed potential but was often slow and less detailed in its responses. The locally hosted DeepSeek R1 (14B) struggled significantly and failed most tasks.
While AI models continue to improve, the best choice depends on specific needs. For coding tasks, Qwen 2.5 Max is an excellent option. For comprehensive programming and design support, ChatGPT o1 is the top recommendation.
Also read – Why Is Nvidia Stock Going Down Today?
People also Ask
1. What is Qwen 2.5 Max?
- Answer: Qwen 2.5 Max is the latest and most advanced version of Alibaba Cloud’s large language model, designed for high-performance tasks like complex reasoning, coding, and multi-modal processing.
2. How does Qwen 2.5 Max compare to its predecessors?
- Answer: Qwen 2.5 Max offers significant improvements in reasoning, coding, and multi-modal capabilities compared to earlier versions, making it more powerful and versatile.
3. Is Qwen 2.5 Max better than Deepseek or other competitors?
- Answer: While performance depends on specific use cases, Qwen 2.5 Max is considered one of the top rivals to models like Deepseek, especially in areas like reasoning, multi-lingual support, and cost efficiency.
4. What are the key features of Qwen 2.5 Max?
- Answer: Key features include advanced reasoning, superior coding abilities, multi-modal support (text, images, etc.), and strong performance across multiple languages.
5. Can Qwen 2.5 Max handle coding tasks?
- Answer: Yes, Qwen 2.5 Max excels at coding tasks, supporting multiple programming languages and offering advanced code generation, debugging, and optimization capabilities.
6. Does Qwen 2.5 Max support multi-modal inputs?
- Answer: Yes, it supports text, images, and other modalities, enabling tasks like image captioning, visual question answering, and more.
7. How does Qwen 2.5 Max perform in multi-lingual tasks?
- Answer: Qwen 2.5 Max supports over 100 languages, making it highly effective for global applications and cross-lingual communication.
8. Is Qwen 2.5 Max suitable for enterprise use?
- Answer: Absolutely! Its robust performance, customization options, and scalability make it ideal for enterprise-level applications, including customer support, content creation, and data analysis.
9. What makes Qwen 2.5 Max stand out from other AI models?
- Answer: Its combination of cutting-edge reasoning, multi-modal capabilities, extensive language support, and cost efficiency sets it apart from competitors like Deepseek.
10. Where can I access Qwen 2.5 Max?
- Answer: Qwen 2.5 Max is available through Alibaba Cloud’s platform, including services like ModelScope and the Alibaba Cloud Console.
11. Is Qwen 2.5 Max free to use?
- Answer: While there are free tiers and trial options, full access to Qwen 2.5 Max typically requires a paid subscription or usage-based pricing.
12. Can Qwen 2.5 Max be fine-tuned for specific tasks?
- Answer: Yes, Qwen 2.5 Max can be customized and fine-tuned for specific business needs, ensuring optimal performance for specialized applications.
13. How does Qwen 2.5 Max handle ethical concerns like bias?
- Answer: Alibaba Cloud has implemented rigorous training and testing processes to minimize biases and ensure responsible AI usage.
14. What industries can benefit from Qwen 2.5 Max?
- Answer: Industries like healthcare, finance, education, e-commerce, and entertainment can leverage Qwen 2.5 Max for automation, insights, and enhanced user experiences.
15. Is Qwen 2.5 Max environmentally sustainable?
- Answer: Alibaba Cloud prioritizes energy-efficient infrastructure and optimized algorithms to reduce the environmental impact of running large models like Qwen 2.5 Max.
Leave a Reply