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Arvind Krishna

Things Arvind Says on Podcasts

Where to Find Them

Arvind Krishna has been a guest on Closing Bell (6 times) , Squawk on the Street (4 times) , Mad Money w/ Jim Cramer (3 times) , Bloomberg Tech (3 times) , Wall Street Week (2 times) , POLITICO Tech (2 times) , Bold Names (2 times) , All-In with Chamath, Jason, Sacks & Friedberg , WSJ Tech News Briefing , Pioneers of AI , Bloomberg Surveillance , Inside the Strategy Room , Smart Talks with IBM , Decoder with Nilay Patel , Hudson Institute Events Podcast , TechStuff , Winning with AI and Masters of Scale .

Recently: “10AM Hour: Stocks Dive as Oil Spikes, Reaction to Meta and Tesla Results, IBM CEO on Demand 10/22/26” on Squawk on the Street (October 2026); “Arvind Krishna & Nikesh Arora: Quantum Threat, Open vs Frontier AI, AI Cyber Warfare & SaaS Collapse” on All-In with Chamath, Jason, Sacks & Friedberg (October 2026); “The era of experimentation is over, with Arvind Krishna, CEO of IBM” on Winning with AI (September 2026); “Strengthening the US-Japan Alliance Through Semiconductor and AI Partnerships” on Hudson Institute Events Podcast (September 2026); “At 115 Years Old, Can IBM Survive the AI Era? CEO Arvind Krishna Makes the Case” on WSJ Tech News Briefing (July 2026); “Masters of Scale: IBM’s $10 billion bet on what comes after AI” on Pioneers of AI (June 2026).

What They Said

“Okay, so I'm going to talk about developer behavior. And since I was one, I'm making fun of myself in a younger age. Developers are lazy. They're going to use the most expensive answer unless you put a control on it. Because it's easy.” — Arvind Krishna, All-In with Chamath, Jason, Sacks & Friedberg

After Krishna predicted that most enterprise token use will move to cheaper open-weight models, a host asked whether the token use left on frontier models is there because it's needed or out of default behavior. This was his answer.

All-In with Chamath, Jason, Sacks & Friedberg · 2026-10-21 Permalink → Listen →
All-In with Chamath, Jason, Sacks & Friedberg Around 11:26 into the episode
Arvind Krishna

…these things is six to 12 months at the most. And so, all those three drive me to conclude. I don't know whether it'll be 75 to 90 percent, but that's the range I would put. Of all token users, we'll go to open weight models for the reasons I mentioned, add it to the reasons that Nikesh mentioned.

Speaker 3

And the token consumption that's left over, is that because you actually need it, or is that because it's a default behavior and people are too lazy to change?

Arvind Krishna

Okay, so I'm going to talk about developer behavior. And since I was one, I'm making fun of myself in a younger age. Developers are lazy. They're going to use the most expensive, the most expensive answer unless you put a control on it. Because it's easy.

Speaker 3

Yeah.

Arvind Krishna

That is going to take it there. So, I would say, if experimentation phase, you allow that to prove it works, and now I've got to put on a cheaper answer, it's probably fine. If it gets me there a lot faster. But doing it for production usage is where I am skeptical that it's of value, except for a…

Speaker 3

Nikesh, you were brought in as one of this small circle of people for Mythos, kind of preview it, be their partner. I'm sure you're now doing that with OpenAI as well. When you're sitting with these guys, is part of you thinking they're looking at my business and they're like, wow, this is a great…

Speaker names from our own diarization · position estimated from where the line sits in the episode
“We could take one of the Chinese open weight models ... and if you run your own GPUs with a little bit of optimization ... we could drop the cost to about $1 to $2 for a million tokens. Which enterprise in the world will not accept a 10 times, or in this case, a 40 times cheaper answer for effectively what can do 95% of the work?” — Arvind Krishna, All-In with Chamath, Jason, Sacks & Friedberg

Asked about open versus frontier models, the IBM CEO compared roughly $20 to $50 per million tokens at the frontier with a self-hosted open-weight model. He added IP protection and geopolitics as further reasons, and estimated that 75 to 90 percent of all token use will move to open-weight models.

All-In with Chamath, Jason, Sacks & Friedberg · 2026-10-21 Permalink → Listen →
All-In with Chamath, Jason, Sacks & Friedberg Around 10:23 into the episode
Speaker 3

…there's pacing the frontier, there's now effectively very reasonable alternatives that are open weight at a minimum. Your philosophy around the entire spectrum, and just give us a sense of how we should think about models and capabilities over the next couple of years. Nikesh, you want to start?

Nikesh Arora

…us, for example, running a defender model, we're most more than likely going to take an open weight model, use our own proprietary data, train it, manage the weights, because that's what gives us the auditability, the explainability, and the open system. We can actually explain how that happened.

Arvind Krishna

…lens to get to the same exact end conclusions. Let's take economics. So, today, $20 for a million tokens for probably generation minus one, 50 if you want to go to the most extreme. We could take one of the Chinese open weight models, take a Kimik3, something, 800 billion parameters, and if you run your own GPUs with a little bit of optimization, but I'm talking like a week of engineering work, we could drop the cost to about $1 to $2 for a million tokens. Which enterprise in the world will not accept a 10 times, or in this case, a 40 times cheaper answer for effectively what can do 95% of the work? So, I think economics is important. The second is going to be: at the end of the day, you just talked previously about chain of thought, not just the end tokens. Well, effectively, then you're giving away your IP if that chain of thought can be captured and logged and audited by somebody else. So, brand and IP is going to drive people to say, I need to run the models on my own. Well, you can't…

Speaker 3

And the token consumption that's left over, is that because you actually need it, or is that because it's a default behavior and people are too lazy to change?

Arvind Krishna

Okay, so I'm going to talk about developer behavior. And since I was one, I'm making fun of myself in a younger age. Developers are lazy. They're going to use the most expensive, the most expensive answer unless you put a control on it. Because it's easy.

Speaker 3

Yeah.

Speaker names from our own diarization · position estimated from where the line sits in the episode

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