Open source AI has crossed a threshold. For years the debate has centered around whether open models could ever compete with closed ones. This is no longer a debate we should be having. Today Mozilla is publishing its inaugural State of Open Source AI report, built on new analysis and a global survey of 950+ developers, showing that open models are no longer playing catch-up. The
performance gap with top proprietary systems like ChatGPT and Claude has narrowed to just 3%, while costs have fallen up to 50x in three years.
But the report also surfaces a harder truth. Open models now power roughly a third of real-world AI usage, but capture only 4% of the revenue. So while the value is there, it just isn’t flowing back into the open ecosystem that made it possible. Meanwhile, the geopolitical picture is shifting fast.
Asia is racing ahead
China and East Asia now lead the world in open source AI adoption, at 89%, far ahead of the West, treating open source as a cornerstone of national strategy. Governments elsewhere are responding, with 12 new national AI strategies launched last year, and 47 countries now restrict foreign processing for critical workloads. The EU, Canada, and India are backing open ecosystems with real public investment, treating AI infrastructure as a strategic asset.
Developers want open models, but they can’t always ship them.
For developers, the appetite for open source is there, and cost and privacy rank as developers’ top reasons for choosing models. But wanting to use open models and running them in production are different things. 79% of developers use open models, yet only 51% have deployed them in production, versus 63% for closed models. As Álvaro Ruiz Cubero of SlashData, which fielded the survey for Mozilla, put it: “this gap indicates that there is not an issue purely of model quality, but of missing infrastructure. Deployment rates for open models barely increase with company size, highlighting a lack of mature tooling and support. At the same time, buyers are prioritising licensing terms (31%) and ownership (26%), signalling a clear shift toward control and flexibility over raw capability.”
The real battle has moved beyond the model
Perhaps the most important finding may be the least obvious. The layer that matters most isn’t the model. It’s the agentic harness: the software between people and models that decides what an AI system can see, remember, and do. Changing the surrounding software can affect performance more than switching the model itself. Whoever controls that layer controls how AI behaves in the world.
Right now, that layer is being built with very few guardrails. Users approve AI agent requests by default up to 93% of the time, with so-called “consent fatigue” going largely unnoticed.
“Open source AI has reached a turning point,” said Raffi Krikorian, Mozilla’s Chief Technology Officer. “It’s no longer about expanding access to models; it’s about who has the power to shape, audit, and improve them. Without investment in the infrastructure, tooling, and governance around open models, we risk locking in a system where only restrictive, closed AI can scale – and that doesn’t serve the public interest, or sovereignty over tech policy decisions.”
Be owners, not renters
Open models offer what a subscription never can: owning your infrastructure instead of renting someone else’s. Companies like Microsoft and Uber are already rethinking their reliance on paid, closed AI tools as the bills add up. The economics are shifting and so is the thinking.
If you’re a CTO, a policymaker, a developer or an investor, this is the report for you. Read it, share it, and help build the infrastructure to make openness usable, not just possible.