Guest says open models’ margins leave room for price competition; closed models may need fine-tuning

Asked whether major labs could lower prices on their own models to hold back the open-model ecosystem, one guest singled out OpenAI as the company doing this most actively. He described a release transcribed as “6.1 tera” as an attempt to compete with Sonnet; the model designation in the transcript is unclear.

The guest said open models still leave substantial room for price competition. In his assessment, operators that own their technology stack can achieve gross margins above 50%, possibly around 70%, on a relatively modern version of a model. He suggested that labs might need to cut prices by another 50% to become fully competitive.

He also connected open-model economics to the ability to pay infrastructure prices of $20–30 per watt, or $30 million per megawatt, if customers can be secured. Participants said this would require substantially lower aggregate margins for AI labs, though they might also face less competition. Another participant added that closed-source models would need some kind of fine-tuning capability to match an advantage available with open source, though closed models do not necessarily offer it.