TLDR
- OpenAI CFO Sarah Friar spoke at Goldman Sachs’ Communacopia + Technology Conference in San Francisco
- OpenAI is targeting chip design, life sciences, and financial services with industry-specific AI
- The Luna model price was cut by 80%, driving roughly a tenfold increase in usage
- Enterprise revenue grew 32% from June to July, outpacing overall revenue growth of 20%
- OpenAI claims deploying Luna is cheaper than running Chinese open-source models via cloud providers
OpenAI’s Chief Financial Officer Sarah Friar laid out the company’s enterprise strategy on Monday, speaking at Goldman Sachs’ Communacopia + Technology Conference in San Francisco.
#Business | OpenAI slashes Luna price by 80%, says it is now cheaper than China’s GLM 5.3
– OpenAI targets specialized industries like chip design.
– OpenAI undercuts rivals on cost, boosts enterprise growth.
– Luna model price cut by 80% led to 10x usage increase.Read More:…
— Moneycontrol (@moneycontrolcom) September 9, 2026
Friar said OpenAI is focusing on specialized industries including chip design, life sciences, and financial services. She said businesses are increasingly looking for AI tools built for specific tasks rather than general-purpose systems.
The company is also testing outcome-based pricing, moving away from charging customers based on usage. Friar said more enterprises are demanding clear returns on their AI spending.
Aggressive Pricing to Fight Off Competition
OpenAI recently cut the price of its lower-cost Luna model by 80%. That price cut helped push usage up roughly tenfold, according to Friar.
OpenAI has scored a major win with 5.6 Luna, not just in terms of PR, but also due to the efficiency that makes it possible to offer the service to everyone for free, as is the case here.
Luna is cheap *and* good (enough) for several tasks. I still find it impressive that a… https://t.co/YWw2XzwLKZ pic.twitter.com/wZ2QlRQJzc
— Chubby♨️ (@kimmonismus) August 19, 2026
She argued that running Luna through OpenAI is cheaper than deploying Chinese open-source models through cloud providers. “If you’re deploying Luna and compare that to (Z.ai’s) GLM 5.3, for example, on a cloud layer, we are cheaper,” she said.
OpenAI faces growing competition from Chinese open-weight models and rivals such as Anthropic. Corporate customers are increasingly asking whether their AI spending is paying off.
Friar also said OpenAI’s coding assistant, Codex, has reached 25 million users.
Enterprise Revenue Outpacing Overall Growth
Enterprise revenue at OpenAI grew 32% between June and July. That outpaced the company’s overall annualized revenue growth of 20% during the same period.
Friar said enterprise and consumer revenue had reached roughly an even split by mid-year. That puts OpenAI ahead of its own target of reaching that balance by the end of 2026.
OpenAI pointed to its own internal use of AI as proof of the technology’s value. The company built its “Jalapeno” chip using its own models, completing the design and sending it to manufacturing, a stage called tape-out, in just nine months.
Open-source and open-weight models have long been seen as cheaper alternatives to frontier models from companies like OpenAI and Anthropic. OpenAI’s pricing moves appear designed to challenge that assumption directly.
The company is positioning itself to grow in sectors where AI can be tied to specific business outcomes. Friar’s comments suggest OpenAI sees enterprise customers as a key driver of future revenue growth.
The combination of price cuts, industry focus, and outcome-based pricing reflects the pressure OpenAI faces to prove its value against a growing field of competitors.
Enterprise revenue growth now outpacing overall growth suggests that strategy may be gaining traction.
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