The Futurist

Open-weight #1 on SWE-bench Pro — built with zero Nvidia GPUs

“The thesis this model bets on: chip export controls do not prevent frontier-class model training, and open-weight frontier models will become the infrastructure layer for commercial software development within 24 months. Both claims are now empirically stronger because of this release — 100,000 Ascend 910Bs producing a SWE-bench leader is the single most important data point on export control effectiveness since the controls were imposed. The second-order effect is the one that matters: if Huawei's Ascend stack is a credible frontier-training platform at scale, the assumption that Nvidia controls the ceiling of what's possible outside the US just broke. The open-weights + MIT license trend is on-time, not early — but GLM-5.1 is the first model to make that trend undeniable at coding-benchmark-frontier quality.”

Cohere's 111B enterprise model: frontier performance on just 2 GPUs

“The thesis Command A is betting on: within three years, enterprise AI adoption will be gated not by model capability but by the organizational ability to deploy models inside a compliance perimeter, and the winner in that market is whoever makes sovereign deployment cheap enough to justify. That's a falsifiable claim and the trend line — edge inference economics improving 2–3x per year while regulatory pressure on data residency intensifies in the EU and APAC — makes it a well-timed bet, not early and not late. The second-order effect nobody's talking about: if two-GPU on-prem becomes the default deployment pattern, the hyperscalers lose the 'just use our API' argument with regulated industries, which shifts significant AI infrastructure spend from cloud consumption to on-premises hardware — and Cohere, not AWS or Azure, owns that positioning.”