GPT-5.6 Sol Ultra just pulled off something that reads like science fiction: it coordinated 64 subagents to prove a math conjecture that has resisted solution for half a century. The headline number isn’t the model’s raw score on a leaderboard — it’s the orchestration. Sixty-four specialized agents, each exploring a branch of the problem, synthesized into a single proof.
What makes this notable is less the math and more the method. Frontier models have been flirting with theorem proving for years, but scaling to 64 cooperating subagents suggests a workflow where a “solver” is really a small organization of models dividing labor the way a research group would. One agent sketches, another checks, a third hunts for counterexamples, and a coordinator decides when the threads converge.
For builders, the takeaway is practical: complex reasoning tasks may be less about one giant model and more about how you choreograph many. If a 50-year-old conjecture fell to coordinated subagents, the same pattern could apply to code migration, formal verification, and multi-step debugging. The frontier is moving from “smartest single model” to “best conductor of a model ensemble.”
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