Potentially the biggest breakthrough in artificial intelligence today is innovative reasoning models.

When DeepSeek released its R1 model, it quickly changed the game. The model, built to deliver high performance at a much lower cost, showed that effective AI doesn’t always need massive resources.

Its release led to a noticeable shakeup in the market, with major tech players experiencing significant share price drops as investors re-evaluated the new competitive landscape.

What sets R1 apart is its ability to deliver cutting-edge performance at a fraction of the cost, with API access priced over 90% cheaper than competitors like OpenAI’s o1 and Anthropic’s Claude 3.5 Sonnet.

The R1 model’s ability to match the performance of the competition, while being more cost-effective and open, has set a new benchmark.

It has forced suppliers along the AI value chain to rethink their strategies and focus on delivering more affordable, efficient solutions.

As the industry adapts to these innovations, both end users and AI application providers stand to benefit from lower costs and improved accessibility.

This shift in the AI market signals a future where practical, efficient models drive real change in business operations.

Alibaba (BABA) is making big moves in AI with its new QwQ-32B model.

The QwQ-32B model, developed with 32 billion parameters, delivers performance comparable to systems like DeepSeek’s R1 with 671B parameters and OpenAI’s o1 mini.

The company recently committed $52 billion over three years to expand its cloud computing and AI capabilities.

Alibaba’s Cloud Intelligence Group has emerged as a central growth driver, fueled by demand for AI solutions.

The segment’s revenue rose 13% year-over-year in its latest quarter, with triple-digit growth in AI-related products for six consecutive quarters.

Key to this success is the Qwen model family, including the newly launched Qwen2.5 Max, which excels in tasks like coding, problem-solving, and multimodal applications.

Over 290,000 companies now use Qwen-based tools through Alibaba’s cloud platform, creating a thriving ecosystem that reinforces customer loyalty and attracts new users.

While early adoption focused on training models, nearly 70% of Alibaba’s recent cloud demand stems from inference, applying trained AI to real-world tasks.

Meanwhile, the company is doing this open-source, which has spawned over 90,000 derivative models globally.

While China’s economic slowdown pressures consumer spending, Alibaba is diversifying through international commerce.

Its cross-border retail arm surged 36% last quarter, with platforms like AliExpress and Trendyol gaining traction.

Though still loss-making due to upfront investments in user acquisition, this segment is projected to turn profitable within a year.

The push aligns with a global B2B e-commerce market forecast to triple to $43 trillion by 2033, reducing reliance on Chinese retail.

Despite these positive tailwinds, the market is still concerned about Alibaba.

We can see what the market thinks through our Embedded Expectations Analysis (“EEA”) framework.

The EEA starts by looking at a company’s current stock price. From there, we can calculate what the market expects from the company’s future cash flows. We then compare that with our own cash-flow projections.

In short, it tells us how well a company has to perform in the future to be worth what the market is paying for it today.

At the current stock price, the market predicts that the company’s Uniform return on assets ”ROA” will fall to around 21% from 42% last year.