Harvey Introduces Harvey Tenet: A Kimi K3 Base Post-Trained with Fireworks for Long-Horizon Legal Agent Work
Harvey has released Harvey Tenet, its first post-trained model, as a research preview as of today. Tenet is a Kimi K3 base post-trained with Fireworks through 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% mor
Harvey has released a specialized legal AI model called Harvey Tenet, which is based on an existing model and has been further trained using reinforcement learning on legal tasks. The model performs significantly better than its base version on legal benchmarks, completing nearly twice as many tasks on one benchmark and showing 20 percent improvement on contract-related tasks. The model is currently available as a research preview only and has not yet been deployed as a commercial product, though Harvey plans to move it from research to production within its platform over time. The release is aimed at helping law firms build their own specialized AI models for tasks like contract review, due diligence, and document analysis.
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