Thomson Reuters launched Thomson, its first proprietary large language model, on August 24, 2026. The company says it built the model in-house from an open-source foundation and spent $40 million on training, talent, and compute—far below the multibillion-dollar investments associated with many frontier-model developers. Thomson Reuters fully owns and controls the model and says it has lower inference costs than comparable frontier models. Thomson was mid-trained and post-trained using proprietary material from Westlaw, Practical Law, Checkpoint, and Reuters, with hundreds of subject-matter experts involved in setting training goals and evaluations. Less than 10% of the company’s content has been used in training so far. Thomson Reuters says early evaluations place the model on par with recent frontier models across a range of tasks, with gains in following complex instructions and reasoning over dense professional content. The model’s first deployment will be in Tabular Analysis within CoCounsel Legal for law firms and corporate legal departments. CoCounsel Legal will continue using multiple models, applying Thomson to tasks where it has an advantage. Thomson Reuters also plans to extend its models across its legal and tax products and add sovereign-AI options. A small open-weight version of Thomson is available on Hugging Face for academic and non-commercial use, while external legal and AI academics evaluate the model.