Thomson Reuters Leverages its World-Class Data Assets to Launch Its Own Frontier Model

TORONTO, August 24, 2026 – Thomson Reuters (Nasdaq/TSX: TRI), a global content and technology company, today announced the launch of Thomson, the company's first proprietary large language model, developed in-house. Frontier labs have typically spent billions of dollars on compute and years of infrastructure investment to reach the frontier. Thomson Reuters took a different path: starting from a strong open-source foundation and investing $40 million to train Thomson into the right intelligence for the jobs that matter most, covering talent and compute. The result is a model Thomson Reuters fully controls, without the heavy inference costs of typical frontier models.多伦多，2026年8月24日 – 汤森路透（纳斯达克/多伦多证券交易所代码：TRI），一家全球内容和技术公司，今日宣布推出Thomson，这是公司首个自主研发的大型语言模型。前沿实验室通常要花费数十亿美元的计算资源和多年的基础设施投资才能达到前沿水平。汤森路透选择了不同的路径：从强大的开源基础出发，投资4000万美元，将Thomson训练成为最关键工作所需的精准智能，涵盖人才和计算。其结果是汤森路透完全掌控的模型，且没有典型前沿模型高昂的推理成本。

As one of the world's leading providers of trusted content and expertise for professionals, Thomson Reuters built Thomson on decades of proprietary content, technology, and domain expertise no other company can match. Training on that foundation is what made Thomson possible: a model built to Fiduciary-Grade™ standards, at a fraction of the typical cost.作为全球领先的专业人士可信内容与专业知识提供商之一，汤森路透基于数十年积累的专有内容、技术和领域专业知识构建了Thomson，这些优势是其他公司无法比拟的。正是基于这一基础的训练使Thomson成为可能：一个按照Fiduciary-Grade™标准构建的模型，而成本仅为通常的一小部分。

“For years, the AI industry has treated scale as the answer: bigger models, more compute, more money. Thomson shows there is another path,” said Joel Hron, Chief Technology Officer, Thomson Reuters. “Start with a strong foundation, specialize it deeply for the work that matters, and you can build intelligence that is highly capable, far more efficient and entirely under your control. We think that changes the economics of professional AI.”“多年来，人工智能行业一直将规模视为答案：更大的模型、更多的计算、更多的资金。Thomson表明还有另一条路径。”汤森路透首席技术官Joel Hron表示：“从强大的基础出发，针对关键工作进行深度专业化，你可以构建出能力强大、效率更高且完全受你控制的智能。我们认为这改变了专业AI的成本结构。”

What Makes Thomson DifferentThomson的与众不同之处

Thomson starts from a strong open-source foundation. What makes it different is what happens next: state-of-the-art mid-training and post-training techniques, drawing on decades of authoritative content from Westlaw, Practical Law, Checkpoint, and Reuters, with hundreds of subject matter experts integrated from the design of training objectives through to the final evaluations.Thomson以强大的开源基础为起点。它的与众不同之处在于后续的步骤：采用最先进的中期训练和后期训练技术，利用来自Westlaw、Practical Law、Checkpoint和Reuters数十年的权威内容，从训练目标设计到最终评估，整合了数百名领域专家。

“Thomson proves what’s possible when you build AI on decades of proprietary content and editorial expertise,” said Steve Hasker, CEO of Thomson Reuters. “That’s an advantage only Thomson Reuters has, and it shows in the results: our early evaluations put Thomson on par with the latest frontier models across a range of tasks. We’re putting it to work in CoCounsel Legal, with more capabilities and sovereign AI options to come. This is the bar we intend to keep raising.”“Thomson证明了当你基于数十年的专有内容和编辑专业知识构建AI时可能实现的一切。”汤森路透首席执行官Steve Hasker表示：“这是汤森路透独有的优势，并且在结果中得到了体现：我们的早期评估显示，Thomson在一系列任务上与最新的前沿模型不相上下。我们已将其应用于CoCounsel Legal，未来还将推出更多功能和主权AI选项。这是我们打算不断提高的标准。”

The model has been trained on less than 10% of Thomson Reuters content so far, and what comes next is not simply feeding it more data. It is continued discovery of new kinds of specialization and understanding, made possible only by building on decades of proprietary content and editorial expertise.到目前为止，该模型仅使用了汤森路透不到10%的内容进行训练，接下来的工作不仅仅是向它输入更多数据，而是继续发现新的专业化和理解方式，这只有基于数十年的专有内容和编辑专业知识才能实现。

AI Sovereignty, and Why It Matters NowAI主权：为何此刻至关重要

Professionals are paying closer attention to questions of AI sovereignty: how a model is trained, what behaviors and biases live inside it, where it runs, and how the privacy of their information is protected. Thomson marks a shift for Thomson Reuters into a world where those questions are answered directly, not left to third parties alone.专业人士越来越关注AI主权问题：模型如何训练、其内部存在哪些行为和偏见、在何处运行，以及他们的信息隐私如何得到保护。Thomson标志着汤森路透进入了一个这些疑问得到直接回答的世界，而不是独留第三方解答。

Thomson shows a meaningful uplift from its base model in instruction following, the ability to execute complex, multi-part professional instructions precisely. It demonstrates an even greater uplift in navigating dense, domain-specific content, the kind of nuanced reasoning the hardest professional tasks require. It is also able to be trained alongside Thomson Reuters proprietary tools like Westlaw and Practical Law, which makes it more sophisticated and nuanced in its work.Thomson在指令遵循（即精确执行复杂的、多步骤专业指令的能力）方面相比其基础模型有显著提升。在驾驭密集的领域特定内容方面，它展现出更大的提升，这正是最困难的专业任务所需的细致推理能力。它还能与Westlaw和Practical Law等汤森路透专有工具一起训练，使其在工作中更加成熟和细致。

The domain-specific gain challenges a common assumption, that the most capable general-purpose models only need access to the right content to perform at an expert level. Thomson Reuters’ early results suggest otherwise. Proprietary training and human subject matter expertise, applied to a strong foundation, produces gains that content access alone does not.领域专属的增益挑战了一个常见假设：即最强大的通用模型只需访问正确的内容就能达到专家级表现。汤森路透的早期结果表明并非如此。将专有训练和人类领域专家知识应用于强大的基础，能够产生仅靠内容访问所无法带来的增益。

Evaluations of Thomson's underlying foundation model are available in the technical report about the model’s development.关于Thomson底层基础模型的评估，可在该模型开发的技术报告中查阅。

Put To the Test经受考验

Ahead of today's launch, Thomson Reuters began opening the model to a group of legal and AI academics for direct evaluation. We will continue to make the model available to external parties to aid in the further validation and development of Thomson over the coming weeks and months. Thomson Reuters is also making a “small” version of Thomson available as an open-weight model on Hugging Face for academic and non-commercial use to further aid in this validation.在今天的发布之前，汤森路透已开始将该模型提供给一组法律和AI学者进行直接评估。我们将继续在接下来的数周和数月内将该模型提供给外部机构，以帮助进一步验证和开发Thomson。汤森路透还在Hugging Face上发布了Thomson的‘小型’版本，作为开放权重模型供学术和非商业用途使用，以进一步协助这一验证。

“I tested Thomson against ChatGPT and Claude using some of the more challenging questions students have asked in my Corporate Tax class. All three models answered the questions correctly, but I preferred Thomson's responses overall. I especially appreciated the links to treatises, which made its responses more transparent and useful for legal work.” - Jonathan H. Choi, Washington University School of Law“我用学生在我公司税务课上提出的一些更具挑战性的问题对Thomson、ChatGPT和Claude进行了测试。所有三个模型都正确回答了问题，但总体上我更倾向于Thomson的回答。我尤其欣赏其引用的专著链接，这使它的回答更加透明，对法律工作更有帮助。——华盛顿大学法学院Jonathan H. Choi”

“Our evaluation found Thomson’s citation quality generally competitive with leading frontier models, even when tested on Canadian employment-law questions without a Canada-specific setting.” - Professor Samuel Dahan, Director, Queen's Conflict Analytics Lab and Cornell Legal AI Lab“我们的评估发现，即使在非加拿大特定设置下对加拿大就业法问题进行的测试中，Thomson的引文质量也普遍与领先的前沿模型不相上下。——女王大学冲突分析实验室与康奈尔法律AI实验室主任Samuel Dahan教授”

Trust as the Real Differentiator信任才是真正的差异化因素

Thomson Reuters is developing domain-specific AI for customers with the highest expectations of trust and accuracy. The AI industry has spent years competing on raw capability. Thomson Reuters is betting the next horizon will be won in the verification layer. This supports the future of Fiduciary-Grade AI™ in practice, the standard Thomson Reuters sets for AI designed for professionals with duties of care and accountability, where almost right is not good enough, and customer data is not used to train the model without explicit consent.汤森路透正在为对信任和准确性有最高期望的客户开发领域特定AI。人工智能行业多年来一直在原始能力上竞争。汤森路透相信，下一阶段的竞争将在验证层面取胜。这支持了Fiduciary-Grade AI™在实践中的未来，这是汤森路透为负有注意与问责义务的专业人士所设定的AI标准：在这里，‘差不多对’是不够的，未经明确同意不得使用客户数据训练模型。

For CoCounsel, and More面向CoCounsel及其他场景

Thomson's first deployment is inside Tabular Analysis in CoCounsel Legal, exactly the kind of high-volume, structured document review where a purpose-built model's advantage shows up immediately. CoCounsel Legal remains multi-model by design, applying Thomson where it delivers the clearest advantage and other leading models elsewhere. Thomson will be available in Tabular Analysis for law firms and corporate legal departments in the upcoming release. There are also plans to extend Thomson models across the legal and tax portfolio with more sovereign AI options to follow.Thomson的首次部署是在CoCounsel Legal中的表格分析功能里，这正是高容量、结构化文档审查场景，专用模型的优势立竿见影。CoCounsel Legal在设计上仍然保持多模型，在能带来最明显优势的地方使用Thomson，在其他地方使用其他领先模型。在即将发布的版本中，Thomson将在表格分析中向律师事务所和企业法律部门提供。汤森路透还计划将Thomson模型扩展到法律和税务产品组合，并随后提供更多主权AI选项。

The launch of Thomson marks a new chapter for Thomson Reuters. The company has always owned the content, the expertise, and the tools professionals rely on every day. Now it owns the model too. Thomson Reuters is no longer only integrating the world's best content, technology and expertise. It is building intelligence that will power the future of professional work.Thomson的发布标志着汤森路透翻开新的篇章。该公司始终拥有专业人士日常依赖的内容、专业知识和工具。现在，它也拥有了模型。汤森路透不再仅仅是整合世界上最好的内容、技术和专业知识，而是在构建将推动未来专业工作的智能。

Thomson Reuters汤森路透

Thomson Reuters (TSX/Nasdaq: TRI) informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. The company serves professionals across legal, tax, audit, accounting, compliance, government, and media. Its products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth and transparency. Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news. For more information, visit thomsonreuters.com.汤森路透（TSX/Nasdaq: TRI）汇聚人们和组织所需的可信内容与技术，以指引前进的方向，帮助他们做出正确的决策。公司服务于法律、税务、审计、会计、合规、政府和媒体领域的专业人士。其产品将高度专业的软件与洞察相结合，为专业人士提供做出明智决策所需的数据、智能和解决方案，并帮助机构追求正义、真相和透明度。路透社是汤森路透的一部分，是全球领先的可信新闻和资讯提供商。如需了解更多信息，请访问thomsonreuters.com。

Media Contact媒体联系人

Ali Hughes
Director, AI and Innovation Communications
Ali.Hughes@TR.comAli Hughes AI与创新传播总监 Ali.Hughes@TR.com