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What changedHarvey’s gross margins reportedly fell to minus 50% as customer usage drove up the cost of renting AI models, according to The Next Web. The legal-tech company then released an in-house model post-trained on Moonshot’s Kimi K3, and its margins recovered, the report says.
That adds a sharper financial detail to the broader move by AI startups towards open-weight or internally developed models. Harvey is not merely choosing a different model supplier for technical reasons. Its model costs were large enough to turn gross margin negative, making model ownership or customisation a direct commercial question.
The report does not provide Harvey’s current margin, the cost of building and running the in-house model, or a like-for-like performance comparison with the rented systems it replaced. It does, however, supply a useful warning for AI businesses: usage growth can make a product more popular while making its economics considerably less charming.
Sources and evidence- AI model costs are pushing startups towards cheaper open weigh: The Next Web reports that Harvey’s gross margins fell to minus 50% because of increased AI model rental costs, then recovered after the company released an in-house model post-trained on Moonshot’s Kimi K3.
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