Harvey's legal model Tenet: post-trained on Kimi K3 with 134 B300 GPUs for 2 months
meliarobin · x · 2026-08-20
Legal AI company Harvey shared an update on its post-training effort, a model called Tenet, built on Kimi K3 as the base in collaboration with FireworksAI.
Key details:
- Rank-64 LoRA over the full network, trained with GSPO using importance-ratio masking
- Compute: 134 B300 GPUs for 2 months
- Achieves SOTA on LAB and generalizes to third-party legal benchmarks (Mercor's Apex Agents Corporate Law, Crosby's Redline Bench, LegalBench) despite not being trained on third-party legal datasets
- Uses domain-specific sub-agents for complex tasks: M&A diligence via an RLM harness for long-horizon tasks (with Baseten), Review Table with specialist models for high-volume structured extraction (with Applied Compute), and firm knowledge capabilities
Related event: Harvey Launches Harvey II Platform and First Self-Trained Legal Model Tenet(7 posts)→
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