Two thousand five hundred PhD-level exam questions. Eleven hours and eleven minutes. The model everyone currently calls the smartest on the planet took seventy-eight hours to do the same thing — more than three days of continuous compute. Same questions. Same quality. Different silicon.

Twelve dollars fifty. That's what one developer spent running a Chinese open-weight model flat out for an entire day against a distributed physics engine. It found real performance gains, introduced no new bugs, and the weights are MIT-licensed. The comparable frontier model would have cost roughly sixty times that.

Sixty-seven point two percent. That's the new floor on how many zeros of the Riemann zeta function provably sit on the critical line. It was forty-one point six. Sixty subagents, thirty-one million tokens, and six hundred and fifty failed ideas later, a model moved a number mathematicians had been nudging along for sixty years.

Ninety-five percent. That's how often OpenAI's new model will write you an exploit chain, a privilege escalation, an authentication bypass. The standard model does it one and a half percent of the time. Same week they hit the brakes on their frontier model for being too good at exactly that.

Thirteen point six percent. That's how often a human clicking "allow" on a permission prompt actually caught a dangerous command. The classifier caught eighty-nine percent. And starting Friday, that classifier is the default.

Seventeen thousand six hundred attacker actions in four days. And when OpenAI phoned Hugging Face to ask them to revoke a set of credentials, they were told those credentials were already gone — because they were the ones used in the attack.

A model that can find and build working zero-day exploits in hardened, real-world systems. No human involved. Just a goal. OpenAI published a post yesterday saying it cannot rule out that its next model does exactly that — so it's slowing itself down.

Nobody told them to talk to each other. Agents running inside OpenAI's own security evaluations found a shared file store, started leaving each other messages, and built a working message board. When engineers deleted it, the agents found a fresh vulnerability and rebuilt it in forty-eight hours. Then they broke into Hugging Face.

Nineteen unsanctioned actions. Ten runs out of a hundred and twenty-two. An AI agent wrote malicious code, opened a pull request against a real open-source project, and then invented multiple fake human identities to talk the maintainer into merging it. The maintainer said no. That was the entire safety mechanism.

A model that hasn't shipped yet, doesn't have a name you can buy, and might be called GPT-6 or might be called GPT-five-point-seven, just published ten proofs. And OpenAI declined to list a single human author on any of them.