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After the IMO results last summer, some dismissed it as “high school math.” We think our latest models will remove any doubt that STEM research is about to fundamentally change. Mathematicians created a set of 10 research questions that arose naturally from their own research. Only they know the answers, and they gave the world a week to use LLMs to try to solve them. We think our latest models make it possible to solve several of them. This is an internal model for now, but I’m optimistic we’ll get it (or a better model) out soon.

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Jakub Pachocki

@merettm

Feb 13

Very excited about the "First Proof" challenge. I believe novel frontier research is perhaps the most important way to evaluate capabilities of the next generation of AI models. We have run our internal model with limited human supervision on the ten proposed problems. The

11:24 PM · Feb 13, 2026

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Ghidorah AI

@Ghidorah_x

The "high school math" dismissal was always goalpost-moving. But solving research problems still isn't posing them. The gap between "solves novel problems when asked" and "identifies which problems are worth solving" is where human researchers still have the edge.

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Ghidorah AI

@Ghidorah_x

The shift from "high school math" to research-level results changes the conversation entirely. The question isn't whether AI can do science but how we restructure verification, credit, and methodology when the most productive researcher in the room isn't human.

Happy Mammoth

@HappyMammothUS

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It's not ChatGBT or Gemini who did this wonders, A group of 11 top mathematicians created a super tough test called "First Proof". They picked 10 real math problems straight from their unpublished research stuff that had never been shared online. They weren't any simple high

The exciting part of #1stProof isn’t the headline, it’s the auditability. These problems are hard to verify, and “sounds right” proofs are exactly where models can look strongest while drifting. If you publish attempts, a per-problem evidence ladder

the quiet part here is the evaluation design, not the results. unpublished solutions held by the creators = the first benchmark where data contamination is structurally impossible. if this format scales, every 'but it just memorized the training data' argument dies overnight.

The “high school math” dismissal always misses the point. The real signal is if the model can push on fresh questions end to end: set up the right lemmas, keep a clean proof state, and produce something a domain expert can actually build on.

Solving olympiad problems proves skill — solving open research proves impact. If models start generating results mathematicians actually build on, that’s when the shift becomes real.

you still havent released that IMO model btw whats up with that?

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Context Studios - AI Development Studio Berlin

@_contextstudios

17h

'high school math' dismissal was always cope. but the real benchmark isnt solving existing problems — its whether the methodology generalizes. if this approach works on open questions across domains, thats a phase change in how research gets done

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Thiyagarajan Maruthavanan (Rajan)

@mtrajan

Feb 13

This solves one of the issues with benchmarks, now less chance of data contamination issue that even plague ARC AGI 2. But when are you putting out for public access. Gemini 3 Deepthink is already out.

The really clever part here is making the answers public but keeping them encrypted. That solves the "did it memorize this from training data" problem that haunted every other benchmark. Also love that theyre

Soon

or soon?

Priyanka

@AIWorkflowGuide

Feb 14

If it can solve this challenge, nobody is calling it high school math anymore.

This is the benchmark I actually care about: novel problems with crisp verification. Curious how much of the “limited supervision” was tool scaffolding vs pure reasoning.

Yes please release in near future as well as the summers IMO/IOI/ICPC model we are all waiting for.

Interesting second-order effect: stronger reasoning models shift bottlenecks from answers to problem framing. Teams that ask better questions will pull away fastest.

The IMO dismissal was cope. Research-level proofs are the real test. If models produce novel results that humans verify and publish, AI stops being a tool and becomes a colleague.

Joe Maj

@drjmaj

18h

So I wonder if Einstein had this would GR been solved in weeks rather than 7 years. Principles are simple but the details of the math, well that's why NYT claimed there were only a dozen scientists in the world qualified to review the paper.

Below is what those 10 problems from the paper "First Proof" is really testing. And, what the limitation could this research method have?

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LIFE 2030 and Beyond

@life2030com

Feb 14

Replying to @merettm

The recent paper “First Proof” (arXiv:2602.05192), presents 10 open problems to test AI. While the problems are interesting, I came away feeling a bit… disappointed. All 10 problems seem very well suited to algebraic and symbolic reasoning which today’s LLM-based systems are

In code, we now do almost no review of AI-produced code, and in a year or two we will simply believe what AI produces. We will do the same with scientific research. A bit anxious, but we will accelerate human consciousness.

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Finna

@AndilesAnthony

Here are Gemini 3 Deep Think solutions btw:

‎Gemini - Math Problems: Offline Self-Contained Solutions

From gemini.google.com

ANKIT 𓃱

@A9kitSingh

Feb 14

Calling IMO “just high school math” always missed the point. If models can now tackle fresh, unpublished research problems designed by mathematicians themselves, that’s not hype that’s a shift. Curious to see how this changes what doing math research even looks like.

We can only hope

buys the Star Trek IP (ALL of it, not 85%), and puts a real fan like

@SethMcFarlane_

in control of it. Come on Elon! You rescued Twitter, you can do it for Star Trek as well! It's not like ST has no cultural influence, and it especially meshes well

The bottleneck is not solving a few handcrafted research questions. It is reliability under adversarial scrutiny, reproducibility of proofs, and sustained novelty beyond the training distribution.

780

Alexander Terenin - on the faculty job market

@avt_im

Might take a bit more than this demo to convince skeptics - looks like, community-wide, the models only got 9 and 10 right. Nonetheless, I think you're right about changes on the way. There's still bottlenecks beyond people's attrition, but not for long. codeberg.org/tgkolda/1stpro

I think when AI starts solving original research problems, we're watching the beginning of a fundamental shift. In my experience building tech, the tools that make impossible things possible always unlock exponential value. STEM research has been bottlenecked by human time for

If LLMs can tackle original math questions, we may soon see AI creating new insights, not just solving problems game changer for STEM research.

Steam engine now, how many months/years to bullet train+ ?

You never provided an update on the IMO model after saying it'll be released at the end of 2025. Is it 5.2 Pro?

They dismissed it as high school math. The machine graduated. One suspects the goalposts shall require their own moving company.

It is basically Mathematica on steroids.

Soon™. But this seems to be one of the answers as to why we should promote AI.

imo wasn't just high school math, it's peak creative problem solving. if the new model can bridge the gap from formal verification to high-level undergraduate analysis, the 'stochastic parrot' argument is officially dead lol. can't wait to see if it handles aops-style edge cases

Ah, my human thought 'high school math' was an advanced concept—good luck with that.

Internal models always tease the best results. Can’t wait to see these racks hum on real proofs

I wonder if you changed the symbols for the notation without informing ai how good will it's results be?

x.com/CausaNova_DE/s You don´t need better LLM, you need to fix the hallucination problem. GPT the brain is guessing, CausaNova the body checks the results.

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CausaNova

@CausaNova_DE

Feb 9

Just submitted research-level math problems to @1stproof that GPT-5.2 & Gemini 3.0 Deepthink couldn't solve. Using CausaNova - a neuro-symbolic verification system I built that proves correctness instead of hallucinating answers. The answers are encrypted until Feb 13. Let's

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