Cloudflare Adds European Models to Workers AI and Launches Multi-Model AI Defense Workshops

Cloudflare Adds European Models to Workers AI and Launches Multi-Model AI Defense Workshops For its Birthday Week, Cloudflare announced the addition of European open models EuroLLM and Apertus to Workers AI, while rolling out hands-on AI defense workshops for public cybersecurity agencies and critical infrastructure operators. EuroLLM (covering 35 languages, including 24 EU official languages) and Switzerland's fully open Apertus model are joining Cloudflare's Workers AI. Cloudflare open-sourced an AI security harness that orchestrates multiple open and frontier models in parallel to prevent dependency on a single AI provider. A new series of hands-on workshops will train government agencies and infrastructure operators on model-agnostic AI defenses, starting in October in Singapore. Expansion of European Sovereign AI Models As part of Birthday Week, Cloudflare integrated two publicly developed European language models into Workers AI. EuroLLM supports 35 languages, including all 24 official European Union languages, and was trained on the MareNostrum 5 supercomputer by an academic and institutional consortium funded by Horizon Europe, EuroHPC, and the European Research Council. Apertus, developed by ETH Zurich, EPFL, and CSCS under the Swiss AI Initiative, is an open, multilingual model trained on Alps across more than 1,500 languages and designed to comply with the EU AI Act and GDPR. Model-Agnostic AI Defenses and Government Workshops Addressing risks where access to frontier models can be suddenly restricted, Cloudflare's security team developed and open-sourced an orchestration harness. The architecture runs multiple models in parallel to search for vulnerabilities, verify discoveries, and prioritize threats without relying on a single provider. In response to government requests, Cloudflare is launching hands-on workshops for cyber agencies and critical infrastructure operators to help them deploy their own multi-model defenses, beginning at Singapore International Cyber Week in October. AI Sovereignty via Decentralization and Open Standards Cloudflare argues that AI sovereignty should focus on choice and open standards rather than isolationist restrictions. Noting that its network operates GPUs for inference in over 230 cities, Cloudflare highlighted existing adoption of regional open models across the Asia-Pacific region and pointed to ongoing engagements, including Matthew Prince's remarks at the India AI Impact Summit and an upcoming summit in Geneva in 2027.

Cloudflare在Workers AI上线EuroLLM与Apertus，并推出多模型网络防御研讨会 Cloudflare宣布在Workers AI中引入欧洲公立科研机构开发的EuroLLM和瑞士Apertus两款多语言开源模型，同时开源多模型AI安全防御框架，并针对政府及关键基础设施运营者推出实操培训研讨会，倡导通过技术选择权保障AI主权与安全。 EuroLLM与瑞士Apertus两款欧洲开源大模型正式加入Workers AI平台开放申请。 Cloudflare开源了能够并行协调多种AI模型的多模型防御框架（Harness），避免依赖单一供应商。 将于10月在新加坡启动面向政府网络部门和关键基础设施的首场AI防御实操研讨会。 上线EuroLLM与Apertus欧洲开源大模型 Cloudflare在Workers AI上线了两款由欧洲公共科研机构训练的模型。EuroLLM支持包括欧盟24种官方语言在内的35种语言，由泛欧科研联盟利用MareNostrum 5超级计算机开发；瑞士的首个完全开源模型Apertus涵盖超1,500种语言，基于超15万亿Token和10,000多块GH200 GPU训练，并在设计上严格遵循欧盟AI法案与GDPR规范。 反思技术筑墙：以多样化选择构筑AI主权 面对前沿模型被用于网络攻击及部分地区访问受限的现状，Cloudflare反对将AI主权视为零和博弈与修筑壁垒。Cloudflare的网络覆盖超125个国家的335多个城市，其中超230个城市配备GPU推理算力，认为去中心化且负担得起的AI访问是国家韧性的关键，任何国家都不应在AI上受制于单一公司。 开源多模型防御框架并开展政府技能培训 鉴于关键模型可能在毫无预警下遭限制访问，Cloudflare安全团队研发并开源了一套编排层框架（Harness）。该框架能够协同多种闭源或开源模型并行寻找漏洞和研判威胁，确保单一模型失效不会导致防御中断。Cloudflare宣布将于10月在新加坡国际网络周举行首期线下实操研讨会，帮助政府机构和关键基础设施搭建自主可控的AI防御架构。

It's Birthday Week, when we traditionally ship presents to the Internet. This year, two of them come from Europe: EuroLLM, which covers all 24 official EU languages, and Apertus, Switzerland's fully open model, trained on more than 1,500 languages. Both were built by public universities and research institutions. Both are coming to Workers AI, and you can request access today. We're also launching hands-on workshops that help government cyber agencies and critical infrastructure operators build AI defenses that work with any model. The first runs in Singapore in October. Today's announcements follow from an argument we made [a year ago](https://blog.cloudflare.com/sovereign-ai-and-choice/), when questions about AI access and sovereignty were swirling in national capitals. Our answer was choice: the freedom to pick the right tools for the job, and to switch when you need to. Since then, those conversations have hardened. Attackers have used frontier models to run cyber attacks. Access to some frontier models now depends on where you are. Calls to restrict open models are getting louder. Put it all together and it's easy to conclude that AI sovereignty is zero-sum: every model another country controls is one you can't count on, so the safe move is to build walls. We think the past year can point the other way. India, Japan and Singapore focused on open-sourced models, and people across Asia-Pacific built tools on them for rural citizens, elderly patients and the nurses who care for them. Our own security team built AI defenses that work with any model, so losing access to one doesn't mean losing your defenses. Helping build a better Internet has always meant more options, not fewer. That's why we work on open standards that prevent [vendor lock-in](https://www.cloudflare.com/learning/cloud/what-is-vendor-lock-in/), why so much of what we build is free to start with, and why our [network](https://www.cloudflare.com/network/) runs in more than 335 cities across 125+ countries, with GPUs for AI inference in more than 230 of them. We don't think any country should have to depend on one company for its AI. That includes us. In February, Matthew Prince told the India AI Impact Summit 2026 in New Delhi that decentralized, affordable access to AI is a matter of national resilience. The models from India, Japan and Singapore we'd added a few months earlier were our first proof. The summit series moves to [Geneva](https://genevaaisummit.swiss/) in June 2027, with a mission of "prosperity and progress for all." [EuroLLM](http://eurollm.io/) supports 35 languages, including all 24 official EU languages, many of which are underserved by existing open models. It was developed with support from Horizon Europe, the European Research Council and EuroHPC by a consortium that includes Instituto Superior Técnico, the University of Edinburgh, Instituto de Telecomunicações, Université Paris-Saclay, Unbabel, Sorbonne University, Naver Labs and the University of Amsterdam. It was trained on the MareNostrum 5 supercomputer and, according to the consortium, outperforms similar-sized models on EU multilingual benchmarks and machine translation. You can request access to EuroLLM on Workers AI [here](https://developers.cloudflare.com/workers-ai/models/eurollm-9b-it/). [Apertus](https://apertus-ai.org/) (Latin for "open") is Switzerland's first large-scale, fully open, multilingual language model. It was trained on more than 15 trillion tokens across more than 1,500 languages, with 40% of training data in languages other than English. It was developed by ETH Zurich, EPFL and the Swiss National Supercomputing Centre (CSCS) as part of the [Swiss AI Initiative](https://www.swiss-ai.org/): built by public institutions, for the public good. Its architecture, weights, training data and methods are all published. It was designed with Swiss and European rules such as the EU AI Act and GDPR in mind, which means respecting training opt-outs, removing personal data and preventing memorization. It was trained on CSCS's Alps supercomputer (more than 10,000 GH200 GPUs), and its developers report that it significantly outperforms leading closed and open models on rare and regional languages, from Romansh and Swiss German to low-resource languages across Asia and Africa. You can request access to Apertus on Workers AI [here.](https://developers.cloudflare.com/workers-ai/models/apertus-v1.5-8b) Last year's national models didn't sit on a shelf. Since we added them to Workers AI, hundreds of students, startups, small businesses and public servants across Asia-Pacific have built on them, many at buildathons we ran with local partners. Three of them: Governments want to use AI to defend essential services and national infrastructure. The frontier models that can find vulnerabilities at scale can find them for [defenders](https://blog.cloudflare.com/vulnerability-discovery-remediation/) too. But a defense built on one model is only as dependable as your access to that model, and governments have watched access to critical models get constrained with little warning. We had the same problem, and in security we are always our own first customer. Over the past year, our Security team, working with teams across the company, set out to build AI defenses that don't depend on any one model. We built a harness: an orchestration layer that coordinates multiple AI models working in parallel to hunt for vulnerabilities, verify findings and prioritize threats. We [published what we learned](https://blog.cloudflare.com/cyber-frontier-models/) about using frontier and open models together, [open-sourced the harness](https://blog.cloudflare.com/build-your-own-vulnerability-harness/) so any organization can run it with the models of its choice, and laid out the [layered architecture](https://blog.cloudflare.com/frontier-model-defense/) we use to stop attackers armed with frontier models from finding vulnerabilities in the first place. Because the harness works with any model, closed or open, losing access to one provider doesn't switch your defenses off. When we walked governments through it, the most common reaction was relief. Then came the practical questions: how to stand it up in their own environments, under their own rules. Briefings quickly turned into requests for hands-on training. So today we're launching a program of hands-on workshops for government cybersecurity agencies and critical infrastructure operators. Participants build their own AI security harness and layered defenses, and leave knowing how to adapt both to their organization. The modules are plug-and-play, designed to slot into national AI skilling and cyber resilience programs. The first workshop runs in Singapore this October, at Singapore International Cyber Week. None of this happened alone. Partners like [CyberPeace](https://cyberpeace.org/) in India and [Code for Japan](https://www.code4japan.org/en) helped turn open models into working tools. If you run a national AI program, a cyber agency or critical infrastructure, and you'd like more options than you have today, write to us at policy-team@cloudflare.com. Request access to EuroLLM and Apertus, or start with the [harness](https://blog.cloudflare.com/build-your-own-vulnerability-harness/). A year ago, we said choice is the path to AI sovereignty. This year showed it's the path to AI security, too.