As the global Chinese community ushered in the New Year, a significant event unfolded on the trading floor of the New York Stock ExchangeIn a dramatic pre-market shift, Alibaba's stock experienced an astonishing surge, climbing from a modest 1% increase to a remarkable 6.7% just before the closing bellThis remarkable fluctuation wasn't merely coincidental; it was propelled by unprecedented advancements in artificial intelligence technology, signaling a pivotal moment in the global market.

On the early hours of January 29, Alibaba's AI team quietly released its latest large model, Qwen2.5-MaxThis groundbreaking model distinguished itself on various authoritative benchmark tests, displaying performance that could rival some of the world's top models, such as DeepSeek and GPT-4. Industry experts quickly began to analyze this development, noting that the previous fixation on DeepSeek had overshadowed the holistic growth of China's AI sector, of which Alibaba is a significant player.

Major tech outlet “Information Equality” remarked that if Qwen-2.5-Max indeed performed at or beyond the capabilities of its competitor, V3, there would be high expectations for its reinforcement learning (RL) reasoning model as well

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With the powerful trio of “robust models, adequate computing resources, and a comprehensive cloud platform,” Alibaba Cloud has captured widespread interest across diverse sectorsThe emergence of this advantage drew comparisons to the landscape of North American cloud service providers in the previous year, prompting an essential question: Does Alibaba Cloud's rise validate the investment tactics that shaped the success of its North American counterparts?

In the previous year, North American cloud service providers attracted substantial investments and experienced rapid growth by strategically positioning themselves within the realms of cloud computing and artificial intelligenceTheir formidable technological infrastructure continually optimized cloud services, enabling businesses and developers to meet diverse needs for data storage, computational power, and AI applications effectively

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Consequently, they secured a competitive edge in the marketAlibaba Cloud now possesses similar advantageous capabilities: state-of-the-art models facilitating precise AI services, sufficient computational resources ensuring efficient data processing and model training, and a comprehensive cloud platform supporting an entire industrial chain from infrastructure to application service.

This parallel in strengths led investors to reassess Alibaba Cloud's value proposition, questioning whether it could replicate the success witnessed in North America's cloud computing sectorThe nuances of this inquiry gain further dimension against the backdrop of an astounding $10 trillion increase in the US stock market fueled by advancements in AI technologySuch staggering figures illuminate the colossal influence AI has exerted over the capital marketUnder these conditions, the spotlight shifts naturally toward the assets within China’s AI sector, raising the question of whether it is time for a revaluation of these assets.

China boasts a vast market demand, a rich pool of talent, and substantial policy support in the AI field

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As Alibaba Cloud and similar enterprises continue to breach new technological and market frontiers, the latent potential within China’s AI assets is gradually being realizedIf China can learn from the developmental narratives of the U.Smarket and capitalize on the opportunities presented by AI advancements, the prospects for a new phase of value reassessment in Chinese AI assets could yield significant returns for investors.

Delving deeper into the specifics of the Qwen2.5-Max model reveals its use of an ultra-large scale MoE (Mixture of Experts) architecture, built on a database of over 20 trillion tokens during its pre-training phasePerformance metrics obtained from testing platforms evaluating college-level knowledge, programming capabilities, and comparative assessments against human preferences reflected a competitive edge against models such as DeepSeek V3, GPT-4, and Claude-3.5-Sonnet

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With the continuous advancement in post-training technology, the team has expressed optimism that upcoming versions will reach even greater heights.

Alongside this release, Alibaba's Qwen2.5 team introduced two innovative models: Qwen2.5-7b-instruct-1m and Qwen2.5-14b-instruct-1mThese open-source models have broken ground as the first publicly available models supporting up to 1 million tokens in a context windowThey employ sparse attention mechanisms to hone in solely on the most critical segments of the given context, achieving processing speeds for 1 million token inputs that are three to seven times faster than traditional techniquesFurthermore, these models can output lengths of up to 8,000 tokens.

In tests involving the examination of extensive documents for hidden numbers, the 14B model and Qwen2.5-Turbo achieved remarkable accuracyThe smaller 7B model also performed admirably, displaying only minor errors

In more demanding evaluations, like RULER, LV-Eval, and LongbenchChat, the million-token model consistently outperformed models limited to 128K tokens, demonstrating significant superiority, especially in sequences exceeding 64K tokensOn the RULER benchmark, the 14B model scored over 90 points, marking a first for the Qwen series and continuing to overshadow competitors such as GPT-4o mini across multiple datasets.

With such striking advancements in technology and performance, a critical examination of the valuation of Chinese AI assets may be timelyIf DeepSeek V3's emergence marked a turning point for Chinese AI's sharpness, Alibaba's latest breakthrough indicates a profound evolution within the industry ecosystem.

On the very day of the Qwen2.5-Max launch, Alibaba Cloud’s Bailian platform also unveiled comprehensive tool chain support, allowing developers to access capabilities directly from the cloud

This trifecta of “supercomputing clusters, open-source ecosystems, and cloud-native architectures” mirrors the business models of leading North American providers AWS, Azure, and GCP.

Furthermore, insights from the latest Morgan Stanley research suggest that high-performance, low-cost models will reshape the landscape of data centers and the broader software industry in ChinaIn the short term, widespread adoption of similar technological routes by large tech firms could diminish the need for AI training; however, in the long term, lower-cost models are expected to stimulate demand for inference, creating favorable conditions for data centers in major urban areasMoreover, the reduction in AI model costs will lower barriers for software applications seeking to integrate AI functions, enhancing the industry’s environment from the supply side.

If Qwen2.5-Max’s performance measures do indeed mirror expectations, alongside its cost-effectiveness and the established cloud ecosystem, a new round of revaluation of Chinese AI assets may be on the horizon, succeeding the recent prominence established by DeepSeek.