On October 6, OpenAI posted 722 mathematical manuscripts grouped into 372 result families to a public GitHub repository

Overview Debates Related claims Topics

OpenAI released automated mathematical results claiming solutions or progress regarding Navier-Stokes, the quasi-Riemann hypothesis, and the Unique Games Conjecture

Grigori Perelman proved the Poincare conjecture by publishing his Ricci flow papers on the arXiv preprint repository in 2002 and 2003

Virginiya Vassilevska Williams and Josh Alman authored a paper demonstrating an asymptotic algorithm improvement for the three-sum problem

In Leash Bio's benchmark experiments, certain language model agents selected molecules that contradicted the agents' own stated structure-activity relationship hypotheses

Claude Sonnet 5.5 achieved strong performance on Leash Bio's chemical exploration benchmark

Kevin Buzzard's research team translated statements of 50 mathematical theorems from the Annals of Mathematics into formal statements checked by AI

On the GDPVAL AA benchmark for agentic white-collar work, Kimi K3.1 ranked behind Opus 5.5 and ahead of Fable 5.1

Claude Sonnet 5 exhibited high operational costs and low performance on Leash Bio's chemical exploration benchmark

In Artificial Analysis testing, Kimi K3.1 scored 64 on the Cyber Index

Leash Bio evaluates agent exploration strategies on structure-activity relationship tasks within fully pre-measured chemical landscapes

Solve 6.1 demonstrated high performance on Leash Bio's chemical exploration benchmark

Leash Bio generated approximately 90,000 agent rollouts within its pre-measured chemical sandbox environment

On the Artificial Analysis Cyber Index, Kimi K3.1 scored 11 percentage points higher than DeepSeek V41 Flash

Artificial Analysis determined that Kimi K3.1 consumes 14% more tokens per task than Kimi K3

Removing molecular structure data from language model context causes agent decision quality to degrade on chemical exploration tasks

On the Artificial Analysis Cyber Index, Kimi K3.1 scored five percentage points lower than the Daybreak Blue partner program version of GPT6 SOL

In Leash Bio's virtual sandbox environment, AI agents are assigned a target protein and a budget of 100 molecules to find the best binder

DeepSeek V41 Flash and GLM 5.3 scored in the low 40s on the Terminalbench 4.0 benchmark

In independent evaluations by Artificial Analysis, Kimi K3.1 scored 55 on the Intelligence Index, ranking fourth behind Opus 5.5, Sonnet 5.5, and Muse

Astra 6 achieved the highest performance among frontier language models evaluated on Leash Bio's chemical exploration benchmark