CNBC's Mackenzie Sigalos reports on how OpenAI is getting more efficient at running its AI, Softbank's OpenAI funding commitment, and more.

The release of Open AI's ChatGPT has accelerated the development of artificial intelligence and warnings about its impact on society.

Rise of AI

OpenAI has raised its compute margin on paid products, including ChatGPT and its API, to approximately 70% as of October, up from 52% at the end of the previous year and 35% in January 2024. This improvement is attributed to a yearlong focus on operational efficiency, including reducing inference costs, optimizing GPU usage, and implementing smarter model routing.

Despite these gains, OpenAI continues to face pressure from competitors like Anthropic and the challenge of supporting a large free user base. The company is also the focus of a major $22.5 billion funding commitment from SoftBank, which is restructuring its investments to support OpenAI's growth and infrastructure expansion.

OpenAI efficiency gains

Welcome back. OpenAI is getting more efficient at running its AI. Our Mackenzie Segalos has that story for us. Hi, Mack. Hey, Mike. One of the biggest questions for OpenAI right now is whether it can make ChatGPC profitable at scale. And that comes down to how efficiently it can run the models. A source close to internal financials tells me OpenAI's compute margin on paid products, we're talking both ChatGPC and the API, jumped to about 70 percent in October, up from roughly 52 percent at the end of last year and about 35 percent back in January 2024. Now, they're attributing it to a yearlong efficiency push, squeezing inference costs, keeping GPU capacity tighter and routing traffic to the right models so that expensive compute isn't wasted. Now, the contrast with Anthropic is striking. The information reported they started last year around negative 90 percent on compute margin, but its internal projections suggest it could eventually beat OpenAI on total server efficiency once you include training and the cost of serving free users. And that's the pressure point for OpenAI. The free user base is enormous. And even at around 70 percent on paid products, that's still well below the kind of margins you see at mature software giants where adding another user, even a free one, costs very little, which brings you straight to the funding question. Reuters reporting that SoftBank is pushing to close that $22.5 billion commitment to OpenAI by the end of the year. And they're doing that by raising cash, selling investments and potentially pulling on undrawn margin loans backed by its stake in chipmaker ARM. OpenAI, remember, is one of SoftBank's biggest all in bets yet. SoftBank's already liquidated its entire NVIDIA stake, trimmed nearly $5 billion in its T-Mobile U.S. position, and cut headcount all to fortify their posture in the AI arms race. Guys? So, Mac, the efficiency gains that OpenAI is talking about here, right, trying to get more out of every unit of computing power, I assume that also would translate back into, therefore, needing less power per search and per unit of whatever they're delivering. I just wonder if that's going to be the battlefront in terms of all these models. And maybe we don't have to extrapolate the massive power usage numbers that we've been seeing. So there are a couple of factors at play on that front. So, one, we talk a lot about the compute buildout and the context of creating this fresh infrastructure. That's where that $1.4 trillion spending commitment from OpenAI comes from. And that's where a lot of these power concerns are derived from. But part of what led to this higher margin is the fact that the cost of renting GPU capacity has dramatically come down this year. And that's part of what led to these healthier margins for them on compute. And then, I mean, the other side of this, Mike, is the fact that the GBT-5 model, a key feature of that launch was the router, and people complained a lot about it. But it's a big reason the compute margin moved higher, because it routes traffic to the cheapest model that can still do the job. Got it. OK, so it isn't necessarily just that somehow they're able to use less juice. Matt, thank you very much.

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