Thomson
Fiduciary-Grade AI for Professional Work
Context window
Not announced
Input / 1M tokens
Not announced
Output / 1M tokens
Not announced
Provider
Thomson Reuters
Data verified 2026-08-25
Thomson is Thomson Reuters' first proprietary large language model developed in-house on an open-source foundation. Trained on decades of proprietary content from Westlaw, Practical Law, Checkpoint and Reuters with a $40 million investment. Purpose-built specifically for professional legal and tax work with domain-specific expertise.
Capability index
Relative estimates (0-100) to place this model against its peers, grounded in published benchmarks.
How to access it
Available through CoCounsel Legal for Tabular Analysis. Small open-weight version released on Hugging Face for academic and non-commercial use. API access portal in development.
Strengths
- ✓Domain-specific expertise in legal and tax work
- ✓Strong citation quality comparable to frontier models
- ✓Cost-efficient alternative to frontier models
- ✓Fully owned and controlled by Thomson Reuters
Best for developers who...
When to choose it (and when not to)
Reach for Thomson when...
- →When domain-specific legal/tax expertise is critical
- →For organizations wanting sovereignty over AI training and deployment
- →When cost efficiency matters alongside accuracy
Look elsewhere if...
- ✕For general-purpose tasks outside legal/tax domains
- ✕If maximum reasoning breadth across all domains is required
How to use it
Quickstart
Not announcedNot announcedAPI access portal in development
API model id: thomson
Benchmarks
| Benchmark | Score | Notes |
|---|---|---|
| Legal Domain Performance | Competitive with frontier models | Citation quality tested on Canadian employment law |
| Document Review Accuracy | Not quantified | Deployed for Tabular Analysis in CoCounsel Legal |
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