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. |
Themes
GS
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Citigroup Earnings Revisions Turn Positive
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P
Everpure Earnings Estimates Improve
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JPM
JPMorgan Earnings Estimates Rise
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UI
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XLK
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Short Tech, Long Energy
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HOOD
Relative preference for Meta over Robinhood
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LITE
MRVL
AI infrastructure CapEx still under-forecast
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SPY
FinX Panic on Market Dip
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GLD
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OUST
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NBIS
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LMND
LLY
TEM
TMDX
UNH
AMD
MU
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Nebius asset-light AI cloud partner model
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SPCX
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NVDA
AI-Driven Expansion of Global GDP
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ASML
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SPY
Short-term equity bounce into week-end
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TIP
VNQ
ARCC
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TLT
NVDA
XLY
Disinflation narrative pivot and rotation away from AI and debasement trades
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LLY
MU
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TKR
6481.T
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GECC
ORLA
HTLD
MEOH
NCNO
JD
BWAY
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FXY
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QQQ
TLT
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TLT
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NVDA
MU
AAOI
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TEM
Tempus AI data and applications revenue scale
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RBC
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URA
SMR
DNN
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MU
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ROKU
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NVGN.MX
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MAGS
SMH
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KRE
IWM
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