Why AI labs are hosting Chinese models to fund their frontier ambitions. Plus, we take a look at MiniMax’s revenue surge.
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IN FOCUS

  • For mid-market AI labs, Chinese models pay the bills
  • MiniMax shows how free AI can also pay

Hello reader,

Four years after ChatGPT's launch, the dust is settling across the hundreds of AI labs worldwide. The market is breaking into clear buckets.

At one end are US frontier labs backed by Big Tech: OpenAI, Anthropic, and Google. At the other are Chinese players such as Z.ai, Moonshot, and MiniMax that have reportedly distilled frontier capabilities into open models that anyone can download and host.

Then come the middle powers. Companies like India's Sarvam and France's Mistral set out to build frontier models, often with a sovereignty pitch.

If the Chinese players weren't in the picture, they might have sold their less-capable models to enterprises that did not need the most advanced US systems but wanted a cheaper, locally hosted alternative. But Chinese models can be downloaded for free and run anywhere, leaving few takers for the middle powers' offerings.

Today's featured story examines their workaround: hosting Chinese models for enterprises on GPUs originally bought to train and serve their own AI models.

This can buy AI labs time by giving them early streams of revenue as they build toward a frontier model. But for many of them, it could signal a complete pivot from model development to an inference cloud business.

Pranav Balakrishnan, AI reporter


TOP STORY

Frontier dreams stall as labs turn to hosting Chinese models

High-end GPUs, which do the heavy lifting, remain scarce and are typically secured through long-term purchases or leases. Though accessed through the cloud, capacity cannot easily be bought and sold on a spot market.

That scarcity has encouraged buyers to lock up more capacity than they immediately need. Hosting Chinese models gives AI labs a way to put that reserved compute to work and generate revenue.

But the business rests on a contradiction, as AI compute is scarce, even as much of it sits underused. That imbalance may not last.


CAN AI COMMUNICATIONS SCALE?

A curated roundtable luncheon by Sinch and Tech in Asia

As AI becomes part of live customer journeys, maintaining reliable delivery and customer trust becomes more complex. Leaders now need to consider whether their communications systems can support growing automation without compromising the experience that customers receive.

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The conversation will cover how to maintain deliverability and channel reliability as automation grows, the role of email in an AI-first world, and the strategic considerations involved in protecting customer trust across increasingly automated journeys.

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SPOTLIGHT

How MiniMax makes money from free AI

The momentum behind open models has become apparent in public markets. MiniMax, which is listed in Hong Kong, said its revenue nearly quadrupled to US$116.6 million in the first half of the year.

MiniMax's business model resembles the one explored in today's featured story. The model weights may be free to download, but enterprises pay for the convenient version: access through the lab's own servers.

Rather than download MiniMax's model and run it on their own GPUs, developers can send requests through its API, asking it to summarize a document or generate code. MiniMax runs the model, returns the response, and charges by usage.

That makes open source less a giveaway than a distribution strategy. The free model draws developers in; the hosted, ready-to-use version generates revenue.

MiniMax's growth points to the changing economics of the AI industry. OpenAI has struggled to meet its growth expectations this year, while leading frontier products such as Anthropic's Fable are facing a market crowded with free Chinese alternatives.


WHEN AI PILOTS STALL, WHAT COMES NEXT?

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Moving from AI pilots to scalable enterprise capability remains a major challenge for enterprises.

This 15 September, during Tech in Asia Conference 2026, Wonderful and Tech in Asia will bring together senior enterprise leaders for a focused discussion called "AI Leaders Breakfast: Closing the Enterprise AI Gap."

It addresses why AI initiatives stall after early testing and examines the requirements across strategy, integration, governance, and organizational alignment needed for enterprise deployment. Expect candid peer exchange, focused discussion, and networking with leaders navigating similar execution challenges.

This session is open exclusively to Tech in Asia Conference 2026 General, Pro, and VIP pass holders. Slots are limited, and all registrations are subject to approval.

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