Alibaba Unveils QwQ-Max-Preview to Compete with OpenAI and DeepSeek

Alibaba has introduced QwQ-Max-Preview, a new AI reasoning model designed to challenge OpenAI and DeepSeek as competition in artificial intelligence intensifies. The model builds on Qwen2.5-Max and represents part of Alibaba’s $53 billion investment in AI and cloud infrastructure, China’s largest private investment in AI computing to date.

The launch comes amid significant shifts in the AI industry. OpenAI recently discontinued its standalone o3 model before its public launch, saying they will integrate its capabilities into GPT-5.

Meanwhile, DeepSeek R1 has gained traction in China, emerging as a key competitor in AI reasoning. With U.S. restrictions tightening on Nvidia’s AI chips, Alibaba’s latest model is built for efficiency, leveraging Mixture-of-Experts (MoE) architecture to reduce computational demands.

<think>…</think> QwQ-Max-Preview

Qwen Chat: https://t.co/FBpr7zfQY6
Blog: https://t.co/Zta7ezuIiC

🤔 Today we release "Thinking (QwQ)" in Qwen Chat, backed by our QwQ-Max-Preview, which is a reasoning model based on Qwen2.5-Max. This model is still for preview. It is highly… pic.twitter.com/eIRP8XGLv2
— Qwen (@Alibaba_Qwen) February 24, 2025

QwQ-Max-Preview and the Shift to AI Reasoning Models

AI reasoning models have become a critical area of competition, with OpenAI, Google, Anthropic, DeepSeek, Alibaba, and xAI all focusing on improving logical problem-solving capabilities.

DeepSeek R1 has positioned itself as a leading AI model in China, surpassing OpenAI’s o1 in structured reasoning tasks and growing in adoption across research institutions and enterprises.

QwQ-Max-Preview follows this trend, utilizing MoE architecture to enhance efficiency. Unlike traditional large AI models, which activate all parameters simultaneously, MoE-based systems selectively activate different sections of their neural network depending on the task. This reduces computational strain, making them more suitable for environments where high-end AI hardware is restricted.

Alibaba states that QwQ-Max-Preview is designed for “complex reasoning tasks, mathematical problem-solving, and high-efficiency coding applications”. The model maintains full OpenAI API compatibility, allowing developers to integrate it into existing AI-powered workflows.

That Alibaba did not share any benchmark results leads to the assumption that it might be underperforming its closest competitors and not bring something groundbreaking new. However, the company shared benchmarks for the underlying Qwen-Max model, which is performing quite well and above DeepSeek-V3 which is the foundation for DeepSeek R1.

Benchmarks for Alibaba’s Qwen2.5-Max model

U.S. Chip Sanctions and China’s AI Strategy

The backdrop to QwQ-Max-Preview’s release is the growing impact of U.S. sanctions on China’s AI industry. The U.S. has banned the export of Nvidia’s most powerful AI chips, including the H100 and A100 GPUs, citing national security concerns. This has forced Chinese AI firms to find alternative strategies for training and deploying models.

As reported in previous coverage, DeepSeek and other Chinese AI companies stockpiled tens of thousands of Nvidia’s downgraded H20 chips before restrictions fully took effect. However, these chips do not offer the same level of computing power, pushing AI firms toward efficiency-driven AI architectures.

Chinese AI developers now have no choice but to design models that perform well on lower-end hardware, given the constraints on advanced GPUs.

DeepSeek’s Expansion and OpenAI’s Business Shift

DeepSeek R1 has emerged as a dominant AI model in China, excelling in structured reasoning and complex logic-based tasks. The company’s rapid adoption has raised questions about whether it leveraged unauthorized training data, prompting OpenAI and Microsoft to launch an internal review. While no official findings have been released, the inquiry underscores growing concerns over AI model training transparency.

As DeepSeek continues to gain market share, OpenAI has made strategic adjustments. The company’s decision to discontinue o3 as a standalone model and integrate its reasoning capabilities into GPT-5 reflects a broader shift in OpenAI’s approach. By consolidating its AI models, OpenAI is streamlining its offerings while reinforcing its position in high-end AI reasoning.

However, OpenAI’s pricing structure is now facing increased pressure. Microsoft’s move to offer free access to OpenAI’s o1 model through Copilot raises questions about how OpenAI will sustain its direct-to-consumer subscription revenue. While OpenAI has continued to monetize GPT-4o and premium-tier AI services, the availability of free alternatives could shift market expectations.

AI Monetization Models Are Evolving

Artificial intelligence firms are taking different approaches to monetization, with a divide forming between subscription-based models and open-access alternatives. OpenAI, Google, and xAI have built their strategies around premium AI services, requiring users to subscribe for access to the most advanced versions of their models. OpenAI’s GPT-4o, for example, remains behind a paywall, limiting full functionality to paying customers.

Chinese AI firms are shifting toward free-tier or open-access models to drive mass adoption. Baidu recently removed subscription fees from its Ernie chatbot, signaling an attempt to compete with DeepSeek by prioritizing accessibility. ByteDance has also expanded AI integration across its platforms, embedding reasoning models into consumer applications to increase engagement.

Alibaba’s strategy with QwQ-Max-Preview follows this trend. By offering an AI reasoning model that is OpenAI API-compatible, Alibaba is positioning itself as an alternative for developers seeking advanced reasoning capabilities without the constraints of OpenAI’s pricing structure.

The Future of AI Reasoning Models

As AI research advances, reasoning models are expected to become a defining feature of AI-driven applications. OpenAI, DeepSeek, and Alibaba are all competing to refine AI logic, improving models’ ability to engage in structured problem-solving. The efficiency-first approach taken by Alibaba and DeepSeek highlights the impact of U.S. chip restrictions on AI development in China, forcing companies to adapt rather than scale up hardware-dependent models.

With Microsoft embedding OpenAI’s models into its enterprise ecosystem, OpenAI’s business model may need to evolve further to compete with free-tier AI solutions. The market will likely see continued experimentation with pricing strategies, accessibility models, and enterprise-driven AI integrations.

Alibaba’s QwQ-Max-Preview represents an expansion of China’s AI capabilities, reinforcing the country’s push toward self-sufficient AI development. Whether this model can rival OpenAI’s and DeepSeek’s dominance in reasoning tasks will depend on adoption rates and real-world performance. As competition between closed and open AI ecosystems intensifies, the global AI market will continue to evolve, shaped by both technological innovation and shifting regulatory landscapes.