Mozilla’s latest report finds open-source models rapidly closing the capability gap with closed rivals, while Europe looks to sovereignty and infrastructure to catch up.
Mozilla‘s latest State of Open Source AI report argues that open-source and open-weight AI have moved beyond experimentation to become a significant part of the global AI ecosystem, driven by rapidly improving capabilities, lower costs and greater control over model deployment.
The September 2026 assessment examines the State of Open Source AI across capability, adoption, infrastructure, investment, regulation and sovereignty, including where Europe is gaining ground — and where it continues to lag behind the U.S. and China.
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Open AI Moves From Promising to Ready
In a letter accompanying the report, Mozilla Chief Technology Officer Raffi Krikorian offers several examples of open AI being developed in Europe. In Lausanne, Switzerland, researchers built an open medical model with the Red Cross, tuned to its humanitarian guidelines, with clinical trials being prepared at home and in Tanzania.
“They built it themselves. They didn’t ask permission, they didn’t rent it — they own it, theirs to run, change and keep,” Krikorian wrote.
He said these aren’t outliers. Open-source and open-weight AI have become one of the fastest-growing builder ecosystems in software history: On Hugging Face alone, there are 2.5 million public models, 13 million users and a presence at a third of the Fortune 500.
On OpenRouter, where developers route real production traffic, open-weight models grew from a sliver of usage to roughly a third by late 2025. Six months later, the platform moves 25 trillion tokens a week — five times more — and the single biggest source of that traffic is an open model.
“This spring, the best closed model scored 60 and the best open models 54. A year earlier, the leading open model scored 22,” Krikorian wrote. “The frontier still leads on the hardest problems — and for the work most builders actually ship, where price, control and deployability decide, the data does not say ‘promising.’ It says ‘ready.’ If you have been waiting for open-source AI to grow up, stop waiting.”
Europe Is in the Open AI Race, but China Leads the Frontier
The report finds that while Europe is present in open AI, it is not leading at the frontier. The strongest open models assessed are overwhelmingly Chinese, with Kimi K3, GLM-5.3 and Qwen 3.8 among the leaders. European player Mistral appears further down the capability spectrum with Mistral Medium 3.5.
Mistral’s openness also comes with commercial restrictions: Mistral Medium 3.5 uses a modified MIT license with a revenue carve-out, illustrating the report’s broader warning that “open weights” and genuinely open-source AI are not necessarily the same thing.
Open AI as a Route to Technological Sovereignty
The report positions open AI as a route to retaining local ownership and control of models, data and infrastructure, rather than renting access from dominant providers.
One example is Switzerland, where a public consortium trained a national model using public supercomputers and released the weights, data and training code, making the model available for others to copy and adapt. Mozilla notes this is unusual: Across the 16 notable releases the report examined, none provided the complete data recipe required by the Open Source Initiative’s definition of open source.
Europe’s Opportunity May Lie Above the Model Layer
The bigger European challenge may be deployment rather than model capability. Globally, 79% of developers surveyed use open models, but only 51% of open-model users get them into production, compared with 63% for closed models.
Mozilla attributes the gap largely to operational tooling and trust rather than raw model performance. That creates an opportunity above the model layer for European companies — particularly in deployment infrastructure, orchestration, compliance, security and enterprise tooling — rather than necessarily trying to build another frontier foundation model.
Economics could also lower the barrier for European entrants. Capable open models can increasingly run on relatively modest hardware, and Mozilla argues that more capability gains are coming from post-training rather than ever-larger pretraining runs. That could shift differentiation toward post-training data, reward design and reinforcement-learning environments, where smaller companies can compete with less capital and compute.
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The UK Bets £500 Million on Sovereign AI
The United Kingdom is backing the development of Lumen Sovereign, which developer Cosine describes as Britain’s first sovereign frontier AI model. The model is being trained entirely on Isambard-AI in Bristol, using compute awarded through the UK government’s £500 million Sovereign AI program.
Thirteen organizations are involved in the design phase, spanning banking, defense, telecommunications and professional services, including HSBC, Lloyds, NatWest, LSEG, BAE Systems, Babcock, BT and the Alan Turing Institute. The report notes, however, that their involvement represents design-phase agreements rather than purchase commitments.
Lumen is being developed using proprietary datasets covering more than 30 regulated workflows and is intended for air-gapped deployment within customers’ own infrastructure by the end of 2026. Because customers must hold the model weights themselves, that requirement effectively excludes API-only providers from such deployments — a restriction Mozilla sees as creating a growing market for open-weight and on-premises AI.
The report also points to Cohere’s plans to roughly triple its UK office footprint as another sign of growing demand for sovereign AI in the country.
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Is the EU AI Act Keeping Pace With Open AI?
The report questions whether the European Union AI Act’s use of training compute as a proxy for systemic risk can keep pace with increasingly efficient models. Sparse models can now achieve comparable capabilities using significantly less compute, potentially placing similarly capable models under different regulatory requirements.
Mozilla also notes that open source does not provide a blanket exemption from the AI Act. Companies that substantially modify or adapt open models for high-risk uses, such as hiring, credit scoring or medical diagnostics, can themselves become responsible for meeting the relevant regulatory obligations.
