❯ Legal AI Firm Harvey Post-Trains Proprietary Model Tenet on Moonshot AI’s Kimi K3

PIVOTLegal AI firm Harvey announced its first proprietary model, Harvey Tenet, built on the open-weight Kimi K3 from Moonshot AI, with inference platform Fireworks AI as training partner. Previously, Harvey had always customized on top of closed-source models from OpenAI, Anthropic, and Google; this is the first time it has swapped its base to an open-weight model from a Chinese lab.

METHODTenet runs on asynchronous reinforcement learning, with training data blending synthetic data, public legal corpora, and human expert annotations. The goal is long-horizon agentic legal work — a single due-diligence engagement breaks down into dozens of steps spanning hundreds of documents. In Harvey’s own published evaluations, Tenet is comparable to frontier models from Anthropic, OpenAI, and Google on multiple legal-agent and knowledge benchmarks. No third-party replication has appeared yet, so these results remain company-reported.

PROCUREMENTHarvey closed a $200 million round in March at an $11 billion valuation, co-led by Singapore’s GIC and Sequoia, bringing cumulative funding past $1 billion; its annualized recurring revenue disclosed in January stood at $190 million, with more than 1,300 institutions and 100,000 lawyers using the platform. A US vertical AI company at this scale is now staking its most critical model layer on a Chinese open-weight foundation — the first time a Chinese lab has entered the training stack of a top-tier US applications company.

▪ SIGNALThe decisive factor for open-weight models isn’t the benchmark leaderboard — it’s whether anyone is willing to put their core product on top of them.