The following article originally appeared on the Tech Policy Press site and is being republished here with the authorâs permission.
In Washington, AI is increasingly being treated as something that needs to be controlled. The government believes that AI is, first and foremost, a national security asset, meaning that it must be sequestered to prevent enemies from gaining an advantage. On the other side of the world, in Beijing, the approach is moving in the opposite direction. China is reducing barriers, encouraging adoption, and using open-source AI as a way to spread Chinese-developed technology across global markets.
There is now a fundamental divide. The United States is betting that control is the path to preserve its lead. China, instead, is betting on diffusion. The country whose technology is adopted most widely may ultimately shape the future of AI. Questions over open source and open weights sit at the center of that contest.
Beginning on July 24, high-profile support for open source moved what is often a debate behind closed doors into the public sphere, where it belongs: Nvidiaâs Jensen Huangâs first-ever post on X linked to an open letter signed by 35 companiesâincluding Palantir, Andreessen Horowitz and Microsoftâwarning Washington not to over-restrict open source software. âOpen models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty,â Huang wrote, leading the likes of Elon Musk and Mark Zuckerberg to post their support.
Mozilla signed it because, despite being a very different company from many of the signatories and not always seeing eye to eye, we believe in the spirit and substance of the letter, particularly that âopenness may be one of the most important paths to AI safety and security.â The letter was followed by the announcement of the Open Secure AI Alliance for AI Safety and Security, which aims to âbuild and share open tools that promote responsible use of and trust in AI.â
The battle is on. Hereâs whatâs behind it.
Following the money
Open models now do about a third of the worldâs AI work, but they collect only about four percent of the money.
Those two numbers, taken from Mozillaâs new âState of Open Source AIâ report, provide more context than the entire AI safety conversation. The report tells a story of a performance gap between open modelsâthe ones whose weights anyone can download, run, and adaptâand the best proprietary systems. While the capabilities are still a jagged frontier, on average, the performance has narrowed sharply over the past year. Costs keep falling. Seventy-nine percent of developers now build with open models. And yet the money hasnât followed the usage.
This is where the battle lies. A third of the work, but only four percent of the moneyâthat gap is the prize.
The battle started almost exactly three years ago, when Anthropicâs Dario Amodei told Congress that advanced open-source AI is on a âvery dangerous path.â On the surface, his argument is pretty simple: once a modelâs weights are public, no one can monitor abuse or revoke access. Once released, an open weights model canât be âunreleased.â But letâs ask ourselves what that revoke switch actually does. Revocation is not a feature of the model, it is in the API contract. That means it only applies to a labâs own customersâand the people in Amodeiâs threat model were never customers. The labs shipping frontier-class open weightsâsuch as DeepSeek, Alibaba, Mistral, and Moonshot (with its just-released, 2.8T-parameter model Kimi)âmostly sit outside Washingtonâs reach anyway. Two million open models already sit on Hugging Face; many run on a laptop. That means that in the real world, thereâs no single kill switch to throw.
This distance between what such a regulatory switch claims to control and what it actually does is whatâs missing from the debate over which models are âsafer.â Itâs also the key to the fight over who captures AIâs value.
To the companies that built the proprietary models, value is about maintaining a privileged position and using everything at their disposal to protect itâpolicy, pricing, and technology. For everybody else, value means the ability and power to shape, audit, and improve the systems we all depend on. And increasingly, that power doesnât live in the model at all.
For instance, right now, two developers can take the identical open model and ship completely different products: a scam-call operation or a nurse-advice hotline. The model doesnât know (or care) about the difference. What is making the actual decisions is the layer of software built around itâthe agentic harnessâthat sits between users and the model, determining what the application can access, remember, and act on.
As models get cheaper, not to mention more interchangeable, that harness is where the power is actually going. And itâs being quietly locked up by the big labs. Farmers know how this story goes. They bought their tractors outright, but the manufacturer kept the keys to the software, making the farmers owners on paper but renters in practice. It took years of lawsuitsâand, just this month, the Federal Trade Commissionâto start prying that lock back open. A similar arrangement is now being built for the software that reads your email, books your travel, and remembers every detail of your life.
This isnât an accident of engineering; itâs a business model. A closed wrapper makes money by making itself expensive to leave. An open one canât lock the door, so it survives only by staying worth using. Same underlying technology, opposite incentives. Itâs the reason the value captured by open models sits at four percent while their usage sits at a third. The real question for all the builders right now isnât which model youâre using. Rather, itâs whether you could leave for a different one.
Guess whoâs deciding the future?
The debate that matters isnât really which models get released or which get regulated; itâs who controls the layer wrapped around them. Thatâs being decided right nowâmostly by developers who donât realize theyâre the ones responsible. For a glimpse of the future, we can look to the internet: it exists as it does today because, when the architecture was still up for grabs, developers chose HTML and HTTP over proprietary walled gardens like AOL. AI is at that same juncture now, and the fact that two million open models already exist suggests plenty of builders have shown up early. That window doesnât stay open on its own, and it doesnât stay open forever. It stays open because people keep choosing it.
For developers, four habits matter most in ensuring an open future:
- Build on open harnesses, not just open models. The orchestration layer above the weights is where capability is concentrating, and closed labs are already welding it shut. Keeping it open takes deliberate effort.
- Own the memory layer. Store accumulated context in portable controllable formats, so itâs retrievable if a vendor changes its terms rather than trapped inside one.
- Keep a second model warm. Integrate an open model and keep it production-ready even while running primarily on a closed API, so switching is cheap if it becomes necessary.
- Donât assume all open stacks are equal. Open models skew toward particular regions and providers; keeping this layer genuinely open means actively supporting a geographically distributed set of options, not defaulting to whichever model is cheapest this quarter.
None of this requires believing anyone is acting in bad faith. Itâs worth noticing, though, that the loudest safety arguments arrived right around the time models got cheap enough for the real competition to move up a layer. Thatâs not evidence of a conspiracyâitâs just where the incentives point, and itâs why so much of the current debate is aimed at the wrong target.
More evidence is in our report, and most of it is good news: performance gaps closing, costs collapsing, millions of developers building. The question in front of developers isnât whether AI is dangerousâitâs whether theyâll hold the keys to the machines theyâre building. The question for governments is whether the keys theyâre reaching for turn anything at all. For now, that door is still open. Letâs work together to keep it that way.
And be sure to join us at AI Codecon: Building with Open Source AI on August 31, a free half-day virtual conference. Youâll hear from leading developers and technical experts working with open-weight models, self-hosted infrastructure, and real-world AI workflows, and learn how building in the open gives teams more control over costs, data privacy, and what they ship. Register today to save your spot.
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