Competitive AI models lift usage and keep inference demand elevated

Conviction: 58% · Horizon: 2Y · 2026-07-17
If Kimi K3 is truly competitive, higher usage expands inference demand rather than cutting infrastructure spend

A genuinely competitive frontier model lowers the barrier to adoption and multiplies workloads. That scales token and GPU-hour consumption, so capex and opex for inference infrastructure can stay elevated even as model competition intensifies.

Instrument Side Target Reason
NVDA Long We believe sustained growth in inference workloads favors suppliers of AI accelerators and the software stack that monetizes GPU capacity, supporting demand for NVIDIA’s data-center franchise over a multi-year horizon.

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