On July 20, Bret Taylor, Chairman of OpenAI’s board, was asked by CNBC about China’s newly launched open-source model, Kimi K3. He responded that when enterprises choose AI models, what truly matters is not whether the model is open-source or closed-source, but whether the token cost incurred delivers sufficient real-world value. In his view, open-source models are not necessarily cheaper, as completing the same task may require consuming more tokens. In contrast, advanced models like those from OpenAI and Anthropic may have higher per-token prices, but they offer greater efficiency and capability. Therefore, evaluating whether a model is cost-effective requires looking beyond per-token pricing to consider the total cost and final outcome of completing a task.
OpenAI Board Chair on Kimi K3: Open-Source Models Are Not Always Cheaper
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Summary
On-chain news reports that OpenAI board chair Bret Taylor told CNBC on July 20 that businesses prioritize token cost value over open-source status. He noted that open-source models may require more tokens for the same task, making them not always cheaper. New token listings from OpenAI and Anthropic, while more expensive per token, deliver superior performance. Taylor emphasized that total cost and outcomes are most critical in model evaluation.
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