UK: gap between open and closed AI models on cybersecurity shrinking

The UK AI Security Institute's analysis reveals a structural shift in the AI landscape: the technical capability gap between closely guarded proprietary models and freely available open-weight alternatives is contracting faster than previously observed. Through 2025, this gap averaged 6 to 10 months; now it has narrowed to 4 to 7 months for cutting-edge capabilities. This trend is driven partly by aggressive open-source development from Chinese firms (exemplified by DeepSeek and Kimi), but the implications extend beyond geopolitical competition.

The significance lies not in the raw performance numbers, but in the control surface. Proprietary models are deployed by a small number of companies that can theoretically gate access, apply safety classifiers, and enforce know-your-customer procedures. Open-weight models, once released, cannot be recalled or centrally controlled. As the gap narrows, widely distributed, uncontrollable AI systems with cybersecurity capabilities—one of the most sensitive domains—become inevitable. The Institute notes that long-horizon cyber tasks (which chain multiple capabilities into full hacking operations) still show a wider gap, suggesting open models may still lack some generalization ability; but this too will likely close over time.