Big tech faces an adapt or die predicament with open weight AI models

Open-weight AI models have rapidly emerged as the latest flashpoint in big tech, with popular Chinese models posing a serious threat to leading walled garden wardens.

Fuelled by an undercurrent of geopolitical jostling between the US and China, models released by the latter’s burgeoning AI industry have had tech giants in a state of red alert in recent weeks.

Kimi K3, a Chinese model developed by Moonshot AI, has wowed users and appears more than capable of going toe-to-toe with some of the best US-made options on the market right now.

Competing with powerful Chinese models isn’t a new experience for the US-dominated AI market, with DeepSeek rocking the market in 2025. What appears to be troubling them – and indeed lawmakers in Washington DC – this time is the fact Kimi K3 is an open-weight model. This means its training parameters (or weights) are publicly available for anyone to download, modify, and run.

That poses a direct threat to major providers intent on keeping enterprise users locked into their own ecosystems. Jeff Watkins, chief AI officer of Leeds-based AI consultancy, NorthStar Intelligence, said these options could offer a more flexible and economically viable alternative to closed-source providers.

This is because enterprises can run open-weight models on their own infrastructure, using their own data. They are also easily customizable, enabling users to tweak them based on changing needs and, crucially, without relying on a single provider.

“Open-weight models are becoming increasingly attractive because they give organizations far more control than closed commercial APIs,” Watkins told ITPro.

“For enterprises, the biggest advantages of open-weight models are control over deployment, upgrades, hosting, data residency, access controls and long-term operating costs.”

“These characteristics make open-weight models particularly attractive for regulated industries where resilience, compliance and predictable operating costs are critical.”

Open source vs open-weight

Open source AI models have become equally attractive to enterprises in recent years, partly for the same reasons: control, flexibility, and independence. Research published in November 2025 found open source AI models perform on-par with closed source options and are typically cheaper.

With the limelight on open-weight options, it’s important to make a clear distinction between them. While there are similarities, open-weight models don’t include the underlying training data used to build them.

This does have benefits though, according to OpenUK CEO Amanda Brock, enabling enterprises to build highly customized models and “giving access to innovation”.

“For innovators, accompanying this with the right documentation enables them to rebuild it into their own model on their own data,” she told ITPro.

“We saw this happen on Hugging Face last year with DeepSeek R1, where the community built Open R1 rather than have to rely on a single model provider,” Brock added. “This is a great example of innovators iterating in the tradition of open source. It also enables products to be built inexpensively for end users, and to give access to all.”

Betting big

The sheer volume of open-weight and open source models now on the market does highlight a growing shift, according to Brock.

The fact that some of the leading models are Chinese-made is equally important, as the country has made a conscious effort to compete with US providers by creating a level playing field.

“China took the decision to shift to a clear open source strategy about eight years ago,” Brock noted. “They’d seen how software has evolved and the US’s position in it.”

“Big tech has been enabled by adopting and using open source, where the software becomes a de-facto standard and those leading in it are central to the ecosystem. A model of open source that’s about big tech collaboration saving costs and building out standards lower in the software stack evolved, and open source offers adoption at a scale that closed proprietary software cannot compete with.”

The stable’s open and the horse has bolted

Watkins echoed Brock’s comments, noting that China’s focus on open-weight AI development “makes strategic sense” and will undoubtedly put pressure on US providers.

Presenting these as viable alternatives fundamentally undermines the image of the US as the go-to marketplace for AI.

“Rather than competing solely through proprietary hosted services, releasing capable open-weight models encourages global adoption, builds developer ecosystems, and creates competitive pressure on US providers,” he told ITPro.

There are signs that this pressure is mounting given recent speculation about a pushback by US authorities. Reports from Axios this month suggested the White House could consider imposing tight conditions, or even restrictions, on US firms working with these models.

These potential moves have a geopolitical motive, but regardless, it’s clear the horse has bolted at this stage.

A host of big tech companies including Microsoft, Nvidia, IBM and more cautioned against “premature restrictions” in an open letter last week. Nvidia CEO Jensen Huang even made an X account to get his message across.

This was followed by another pan-industry call to support open-weight models in response to the OpenAI-Hugging Face incident, in which the latter was forced to use a Chinese-made model to stop the hack.

There is a certain irony that a security incident involving a leading US AI provider has spurred on industry-wide support for the same models that are spooking US authorities.

Watkins suggested that the US AI industry now faces an uncomfortable truth. It may have led the generative AI boom, but it now has to compete with an ecosystem of models designed to undercut it.

“Chinese providers have demonstrated that frontier-quality AI is no longer exclusively a US capability,” he told ITPro.