IBM CEO says businesses prefer open-weight models to costly frontier AI
IBM chief executive Arvind Krishna told investors that many enterprises are shifting to open‑weight AI models because they can deliver roughly 90% of the performance of leading closed models at about 10% of the cost. He said the token cost of running these models is now between 25% and 10% of what frontier LLMs charge, and a typical large company can start with two or three racks of hardware.
Key points
- Krishna says open-weight models cost 10% of frontier models while delivering about 90% of performance.
- He notes performance gap narrowed from 70‑20/30 in 2024 to 70‑50 in late 2025, aiming for 100‑90 soon.
- Enterprises can run open-weight models on two‑three racks, using 10‑25% of token cost, enabling on‑premise AI sovereignty.
Krishna noted that the performance gap has narrowed: in 2024 the best closed model might score 70 while an open model scored 20‑30, but by late 2025 the gap was more like 70 versus 50, and he expects future scores of 100 versus 90. While some tasks still need expensive frontier AI, most workloads can be handled by cheaper, on‑premise alternatives, which also address growing concerns about data sovereignty and control over AI logs.
IBM CEO says businesses are choosing open-weight models over expensive frontier AI
hotminute.co.uk · 23 October 2026
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