Harvey has released Harvey Tenet, its first post-trained model, as a research preview as of today. Tenet is a Kimi K3 base model post-trained with Fireworks using asynchronous reinforcement learning on long-horizon legal work. The training corpus combined synthetic data, publicly available legal data, and human expert data. Harvey states no customer data was used.
Against the base K3 model, Tenet completes almost twice as many held-out tasks on Harvey's Legal Agent Benchmark (LAB) and 20% more on LAB: Contracts, raising all-pass rates by 9 and 2 percentage points, respectively. Harvey reports state-of-the-art results on LAB: Contracts and second place on LAB. The gains also transferred, untrained, to Mercor's APEX Agents and Crosby's Redline Bench.
The stated goal is twofold: build frontier legal intelligence on open-weight models, and give law firms a path to own their own specialized models.
Is It Deployable?
Not yet. Harvey Tenet is a research preview announced on August 20, 2026. Harvey has not published weights, a model card, or an API endpoint. The base model is open-weight; Tenet itself is Harvey's own checkpoint, and the company says the work will move "from research to production" inside Harvey's products over time. What ships today is the recipe, not the artifact.
via MarkTechPost