Thomson Reuters model releases

Thomson Reuters' first in-house proprietary large language model, launched August 24 2026. Built by starting from a strong (undisclosed) open-source foundation and applying state-of-the-art mid- and post-training on decades of proprietary Thomson Reuters content — Westlaw, Practical Law, Checkpoint, and Reuters — with hundreds of subject-matter experts involved from training-objective design through final evaluation, to the company's 'Fiduciary-Grade' standard. Total training investment is reported at ~$40M (talent + compute), positioned as reaching frontier-level quality at a fraction of typical frontier cost while remaining fully owned and controlled by Thomson Reuters. The company claims early evaluations put Thomson 'on par with the latest frontier models' across a range of tasks, with notable domain-specific uplift in instruction following and dense professional-content reasoning — vendor claims, corroborated only by limited external academic testing at launch and with no public benchmark table, so treat as unverified. Model size, architecture, and context window are undisclosed. First deployment is inside Tabular Analysis in CoCounsel Legal (which remains multi-model by design); broader rollout across the legal and tax portfolio plus sovereign-AI options is planned. A smaller version is being released as an open-weight model on Hugging Face for academic and non-commercial use; the flagship remains proprietary and product/API-only.