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How might hardware or on-prem options offered by these companies affect total cost of ownership when using token-efficient models?

Hardware or on-prem hardware options can substantially lower total cost of ownership by cutting the raw running costs that token-efficient models still incur at scale. For example, a related article titled "Phison unveils solution to reduce $3m cost of upcoming 1T parameter AI model to $100K" shows hardware improvements can reduce operational costs dramatically, meaning token efficiency plus better hardware or on-prem deployments can together shrink TCO significantly. Answered

AI models could soon get cheaper as OpenAI, Meta, and xAI enter a new price war

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