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Leaked internal benchmarks for GPT-5.2 “Thinking” have been posted by Sam Altman, and quite frankly, the numbers are ridiculous. We aren’t talking about incremental gains here.
For some reference:
AIME 2025: 100.0%. It solved it. This is a big math test and it means that competition math is effectively “completed” for this model.
ARC-AGI-2: This is the big one for the AGI purists. It jumped from 17.6% (GPT-5.1) to 52.9%. That is a massive leap in abstract reasoning and generalization—historically the Achilles’ heel of LLMs.
GDPval (Knowledge Work): This is the metric that matters for the economy. It flew from 38.8% to 70.9%.
It’s also worth noting that this highlights that scaling and reasoning are both advancing as this is a model that uses maximum reasoning efforts. Lately, it looked like OpenAI got caught with its pants down because Gemini scaled and it worked but this shows that reasoning is doing things that looked impossible.
For users, the thinking models aren’t that popular because they’re slow for every day tasks to replace Google but for innovation, this is huge. What the dual-releases show is that both tracks are still working. Ultimately, there will be a ‘best of both’ that unlocks something beyond this.
This is also big for the economy. GDPval tests well-specified knowledge work tasks spanning 44 occupations.
At the moment, this release is being rolled out and we’re going to see if the use cases match the numbers. What we aren’t seeing is what the lesser models do. This release includes 5.2 Thinking but also GPT‑5.2 Instant and Pro.
What OpenAI says:
“Overall, GPT‑5.2 brings significant improvements in general
intelligence, long-context understanding, agentic tool-calling, and
vision—making it better at executing complex, real-world tasks
end-to-end than any previous model.”
That’s exciting but this screenshot is also making the rounds:
This article was written by Adam Button at investinglive.com.
Leaked internal benchmarks for GPT-5.2 “Thinking” have been posted by Sam Altman, and quite frankly, the numbers are ridiculous. We aren’t talking about incremental gains here.
For some reference:
AIME 2025: 100.0%. It solved it. This is a big math test and it means that competition math is effectively “completed” for this model.
ARC-AGI-2: This is the big one for the AGI purists. It jumped from 17.6% (GPT-5.1) to 52.9%. That is a massive leap in abstract reasoning and generalization—historically the Achilles’ heel of LLMs.
GDPval (Knowledge Work): This is the metric that matters for the economy. It flew from 38.8% to 70.9%.
It’s also worth noting that this highlights that scaling and reasoning are both advancing as this is a model that uses maximum reasoning efforts. Lately, it looked like OpenAI got caught with its pants down because Gemini scaled and it worked but this shows that reasoning is doing things that looked impossible.
For users, the thinking models aren’t that popular because they’re slow for every day tasks to replace Google but for innovation, this is huge. What the dual-releases show is that both tracks are still working. Ultimately, there will be a ‘best of both’ that unlocks something beyond this.
This is also big for the economy. GDPval tests well-specified knowledge work tasks spanning 44 occupations.
At the moment, this release is being rolled out and we’re going to see if the use cases match the numbers. What we aren’t seeing is what the lesser models do. This release includes 5.2 Thinking but also GPT‑5.2 Instant and Pro.
What OpenAI says:
“Overall, GPT‑5.2 brings significant improvements in general
intelligence, long-context understanding, agentic tool-calling, and
vision—making it better at executing complex, real-world tasks
end-to-end than any previous model.”
That’s exciting but this screenshot is also making the rounds:
This article was written by Adam Button at investinglive.com.
When Mark Carney pulled off an improbable election win this year, he didn’t earn a majority in parliament. That means his government could fall at any time, but he came very close.
The Liberals won 169 seats, just three short of a 172 seat majority. In early November, Conservative MP Chris d’Entremont crossed the floor to join the Liberals. That got them to 170. Just now, Michael Ma (MP for Markham-Unionville) announced that he is switching from the Conservatives to the Liberals.
That gets them to 171, just one seat shy.
There are rumors they are courting others and if they get there, that will give Carney enough votes to survive another three years, at minimum. Even without that, now he just needs the support of one other voter to get any legislation passed.
This move will also raise the stakes in any future by-elections as that could flip the numbers.
This article was written by Adam Button at investinglive.com.
When Mark Carney pulled off an improbable election win this year, he didn’t earn a majority in parliament. That means his government could fall at any time, but he came very close.
The Liberals won 169 seats, just three short of a 172 seat majority. In early November, Conservative MP Chris d’Entremont crossed the floor to join the Liberals. That got them to 170. Just now, Michael Ma (MP for Markham-Unionville) announced that he is switching from the Conservatives to the Liberals.
That gets them to 171, just one seat shy.
There are rumors they are courting others and if they get there, that will give Carney enough votes to survive another three years, at minimum. Even without that, now he just needs the support of one other voter to get any legislation passed.
This move will also raise the stakes in any future by-elections as that could flip the numbers.
This article was written by Adam Button at investinglive.com.
The idea of dominance is that AI will be iterative, so the latest generation of AI designs the following one and that also maps to the physical world. I have a hard time believing that it won’t be diffuse as the stakes are so high and the information nearly impossible to protect. Moreover, the world can only accept change so quickly.
At the same time, there is a limit in real world applications. Once a car learns to drive a car, it’s learned. Maybe you can refine it and make it more efficient but in time — and probably not a long time — others catch up. Perhaps you could ‘dominate’ for a time but only if you’re essentially giving it away or using some kind of regulator capture that’s hard to push across borders.
Moreover, I continue to believe that the black swan of this century will be the collapse of the intellectual property system.
This article was written by Adam Button at investinglive.com.
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