OpenAI pushes cost-per-task pricing as it expands into chip design and finance

OpenAI is expanding its advanced models into chip design, life sciences, and finance, arguing that a model with a higher upfront cost can pay off by performing a task with fewer tries.

Reuters reported on September 9 that CFO Sarah Friar made this argument at Goldman Sachs’ Communacopia + Technology Conference in San Francisco on September 7.

For businesses trying to decide between high-end and low-cost models, this alters the debate. Instead of asking which model has the lowest token price, OpenAI would like customers to consider which model offers the cheapest completed task.

Chip design as a wedge, not an EDA replacement

OpenAI is not attempting to supplant electronic design automation systems that engineers are currently employing to develop chips. Its solutions, in fact, assist in enhancing those processes by helping the engineers analyze problems, evaluate approaches, and speed up certain jobs.

According to Friar, the demand for AI developed for specific tasks is growing. As has been reported by Reuters, OpenAI is also testing a business model where pricing depends on how effective the AI is for the given company rather than on consumption.

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