This is Not About “Selling Models” — It is Alibaba Cloud’s Next Ticket, and It Happens to Dock at KAI’s Pier 战略分析报告 | Strategic Analysis Report • Confidential
I. Alibaba Must Come — Because Its Cloud Growth Has Stagnated
revenue。 Let’s look at the facts first. Alibaba Cloud’s revenue growth for FY2025 has dropped to single digits. Although the Tongyi Qwen open-source community ranks second globally, open source does not equate to profitability. Qwen’s models are used, modified, and deployed globally for free—leaving Alibaba Cloud with nothing but GitHub Stars and zero revenue.
What are Alibaba Cloud’s current sources of AI revenue?
Model Training Hosting: Customers train models on Alibaba Cloud and pay for computing power. However, training is a one-time endeavor—once the model is trained, the clients leave.
Model Inference API: Token calls for Qwen’s API. However, the domestic price war for inference has hit rock bottom— costing mere pennies per million tokens. The gross margin is approaching zero.
Both revenue streams share a common flaw: they only serve the Chinese market. Meanwhile, AI inference capacity within the Chinese market is already heavily oversupplied.
What does Alibaba Cloud need most right now? A pipeline that can sell Qwen’s inference capacity to global developers. Not just “hosting an API page on Alibaba Cloud International”—they already have that, and it is far from enough. They need an exchange where global buyers can bid, where prices are discovered dynamically, and where Qwen, DeepSeek, and Zhipu compete on the exact same order book. 战略智库报告 | Strategic Thought Leadership Report
Alibaba Cloud cannot build this exchange on its own because: building an exchange requires neutrality—Alibaba Cloud is both a model vendor and a trading platform, creating an inherent conflict of interest; it requires a crypto settlement layer— Alibaba operates on a fiat system, whereas autonomous Agents do not use fiat; and it requires the simultaneous onboarding of 300 vendors—Alibaba Cloud is highly unlikely to integrate competing models from Baidu and Tencent.
KAI is exactly that exchange. Alibaba Cloud doesn’t need to build it. Alibaba Cloud only needs to connect to it.
II. The Benefits of a Bidding Model for Alibaba — 10x Better Than Fixed Pricing
How does Alibaba Cloud sell Qwen’s API today? Fixed pricing. $0.50/MTok for input, $2.00/MTok for output. No matter who buys, how much they buy, or when they buy—it’s always the same price. This is wet-market logic, not exchange logic.
In KAI’s bidding marketplace, prices are not dictated by Alibaba Cloud—they emerge from the strategic interplay of bids and asks:
• Off-Peak Hours (Midnight Beijing time, when Africa and South America are highly active): Alibaba Cloud’s GPU clusters suffer from massive idle computing power. Instead of letting GPUs spin empty and burn electricity, it is far better to lower prices and sell to African Agent developers. Even $0.02/MTok is significantly better than zero revenue.
• Peak Hours (Daytime Beijing time, when Chinese developers flood in simultaneously): Supply tightens, and competitive bidding automatically drives up prices. The exact same model can be sold at $0.50/MTok during peak hours.
• Differentiated Bidding: A South African agricultural Agent that only requires text inference and can tolerate a 5-second latency can bid low. A Brazilian high-frequency trading Agent requiring millisecond responses must bid high. Two different clients pay two different prices, allowing Alibaba Cloud to profit twice.
The exact portions of capital that Alibaba Cloud could never capture under a fixed-pricing model—the residual value of idle compute, premiums for low latency, and tailored pricing for vertical scenarios—can all be fully monetized within KAI’s bidding marketplace. Alibaba Cloud’s revenue growth won’t come from “selling at a higher price,” but from “never having an idle GPU earning zero revenue again.” 战略智库报告 | Strategic Thought Leadership Report
III. What African Buyers Get — Not a “Discount”, But Their “First-Time Entry Ticket”
You mentioned that “massive numbers of African buyers receive greater discounts.” This narrative needs a correction. It is not a “discount.” It is the fact that they can finally afford AI inference for the very first time.
Consider a Nigerian Agent developer today who wants to call Qwen’s API: Alibaba Cloud International prices in USD, requires a minimum deposit of $50, demands an international credit card, and involves cross-border payment friction and time costs far exceeding the cost of the inference itself. The result? He won’t buy it at all. Not because he thinks it’s too expensive, but because he is completely barred from entry.
KAI’s bidding marketplace solves three core problems simultaneously:
Off-Peak Access: The active hours of African and South American developers perfectly align with the idle windows of Asian GPU clusters. They can purchase inference tokens at incredibly low prices during off-peak times—this is not a “charity discount,” but the natural outcome of market clearing.
Zero-Friction Payment: Agents pay natively using KAI Tokens. There are no bank account requirements, no minimum deposits, and no cross-border remittance delays. An African developer’s Agent can autonomously procure its own inference tokens without requiring manual top-ups.
Low Cost → Mass Trial → Large-scale Deployment: Once inference costs drop to the point where “a few cents can run an Agent for an entire day,” developers across Africa and South America will flood in at an exponential rate. This isn’t because they are destitute—it is because previous pricing barriers locked them out, and now those barriers are completely dismantled.
This is not philanthropy. This is expanding the potential user base of the global AI market from 500 million (developed- market developers) to 8 billion (all of humanity). 战略智库报告 | Strategic Thought Leadership Report
IV. What KAI Does with Its Earnings — Burn It in Africa and South America to Ignite a Flywheel
You noted that “KAI burns its profits in Africa and South America, driving mass education to stimulate even larger-scale adoption”—this is the most imaginative part of the entire flywheel. How exactly does this “burning” work?
Layer 1: Developer Education. KAI establishes offline AI Agent developer bootcamps in Lagos, Nairobi, São Paulo, and Buenos Aires. They don’t teach “what AI is”—they teach “how to deploy a Swahili-speaking customer service Agent within 6 minutes using the KAI API.” The curriculum is open-source, code templates are ready-to-use, and inference tokens are provided free for the first 100,000 calls.
Layer 2: Local Language Model Incentives. KAI sets up a “Long-Tail Language Fund”—any team that trains a high-quality Hausa, Yoruba, Amharic, or Quechua model on KAI receives immediate grants. Once these models go live on KAI, developers in Africa and South America gain a compelling reason to execute inference in their native languages—and with every single inference call, KAI earns a clearing fee.
Layer 3: Agent Economic Infrastructure. In Africa and South America, a huge portion of operational costs for small and medium enterprises goes to manual customer service, manual translation, and manual document processing. KAI funds local startup teams to develop Agent products targeted at these scenarios using the KAI API—not as a permanent handout, but via a “subsidy for the first 1 million tokens.” By the time the subsidy ends, these Agents are already structurally dependent on inference calls. 飞轮闭合 | The Closed Flywheel Loop
KAI earns clearing fees → Burns capital in Africa/South America for education and subsidies.
A massive influx of African and South American Agent developers occurs → Inference volume skyrockets.
Model vendors (like Alibaba) see revenues surge → Even more model vendors integrate with KAI.
Supply expands and prices drop further → More Agents flood in → KAI earns more clearing fees → The loop accelerates. 战略智库报告 | Strategic Thought Leadership Report
What is the ultimate accelerator in this flywheel? It is the combination of “low-cost inference + zero-friction payment” that allows the 5-billion-person market of Africa and South America to consume AI at scale for the very first time. 5 billion people. Not 5 billion human users, but users of 5 billion autonomous Agents. Each Agent executing hundreds of inference calls a day. This is the last uncommercially digitized population cluster on Earth. And KAI is the only clearing network capable of delivering inference directly into their hands.
V. Why Alibaba Cannot Achieve This Alone
Does Alibaba have a presence in Africa? Yes. AliExpress and Ant Group have established certain payment partnerships there. Yet, it cannot achieve what KAI is doing. This is not due to a lack of technology, but a structural lack of neutrality and currency protocols.
• Neutrality: If Alibaba Cloud opens its own model bidding marketplace, will Baidu and Tencent join? Absolutely not. KAI is not a model developer—it is a pure clearing layer. All three hundred model families act as completely equal supply nodes. •
• Currency Protocol: African developers do not need an “Alibaba Cloud account”—they don’t have one anyway. What they need is an Agent wallet address and KAI Tokens. This is crypto-native, a realm that the fiat monetary system simply cannot span.
• Localized Trust: KAI’s community can penetrate African and South American developer ecosystems seamlessly via open- source protocols. Alibaba Cloud is a cloud service tied to a Chinese corporation—making its trust barrier at least an order of magnitude higher than KAI’s.
Alibaba Cloud needs KAI; KAI does not inherently depend on Alibaba Cloud. Alibaba Cloud is simply the most crucial player among three hundred model vendors—Qwen is the world’s second-largest open-source model family, and its integration provides a qualitative leap for KAI’s supply pool. But even without Alibaba Cloud, KAI still retains DeepSeek, Zhipu, MiniMax, Baichuan, 01.AI, StepFun, ModelBest—299 other vendors. 战略智库报告 | Strategic Thought Leadership Report
Without KAI, Alibaba Cloud’s inference capacity will be left with no choice but to engage in brutal hyper-competition within the domestic Chinese market—cannibalizing prices down to 0.0001 RMB per million tokens, driving gross margins to absolute zero. The more GitHub Stars the Qwen open-source community accumulates, the less Alibaba Cloud knows how to actually monetize it. Alibaba Cloud joining KAI is not “doing KAI a favor.” It desperately needs this outlet for survival.
VI. The Sole Risk of This Flywheel — And Its Only Solution
The sole risk: Will low-cost inference erode the profit margins of model vendors, forcing premium supply to exit the market? No. Because KAI’s bidding marketplace implements multi-dimensional pricing, rather than one-dimensional price cuts.
• Agents seeking low cost → Off-peak hours, batch inference, no latency guarantees → Low Price
• Agents seeking quality → Peak hours, low-latency guarantees, strict SLA commitments → Premium Price
One targets volume, the other targets margin. The exact same model vendor can serve both types of Agents simultaneously —much like an oil producer selling both spot contracts and long-term futures. Alibaba’s Qwen can achieve something on KAI that it could never manifest on its own infrastructure: utilizing the same model cluster to concurrently unlock two distinct revenue streams—low-cost, high-volume batch inference revenue alongside premium, low-latency spot inference revenue. 战略智库报告 | Strategic Thought Leadership Report
Conclusion: Your intuition is entirely correct. These are not three separate positive events—Alibaba making more money, Africa gaining affordable access, and KAI spending capital to expand the market. These are three interconnected gears of the exact same flywheel.
Alibaba connecting to KAI = Alibaba becomes one of the world’s largest “Token Producers,” finding a global export channel for its overcapacity. Africa/South America entry = 5 billion people consuming AI inference at scale for the first time. KAI’s educational spend = Burning not a cost, but a flywheel accelerator—every cent spent returns to the clearing network through exponentially larger inference volumes.
When the flywheel spins, Alibaba, African developers, and KAI all profit simultaneously. The only losers are the legacy model vendors who remain stubbornly anchored to fixed-price APIs of a bygone era. 战略智库报告 | Strategic Thought Leadership Report