Wells Fargo Lifts Nvidia’s Price Target to $220
Wells Fargo analyst Aaron Rakers raised on August 11, 2025, its price target for Nvidia to $220 (from $185), maintaining an ‘Overweight’ rating on the stock.
“With strong intra-qtr demand data points + reports of approved licenses to resume H20 sales into China, we increase our ests (above street) ahead of NVDA’s upcoming (8/27) F2Q26 print.
Increase PT to $220, ~29x CY27 EPS at $7.55 (Street @ $6.73/sh.).
Increase Estimates (Above Street)
Strong intra-quarter data points (see below) drive increased F2Q26 ests above NVDA’s $45.0B +/-2% guide – moving to $48.2B / $1.06(prior @ $45.8B / $1.00).
This reflects increased Data Center rev est to $43.1B (prior @$40.7B; street @ $41.1B).
We increase our FY26, FY27, and FY28 ests from $200.6B / $4.37, $256.9B / $6.00, and $303.1B / $7.05 to $210.9B / $4.62, $286.2B / $6.65, and$328.7B / $7.55, respectively.
We increase our FY26, FY27, and FY28 Data Center rev to $190.2B (+65% y/y), $264.5B (+39%), and $305.5B (+15%) vs. our prior $179.8B, $235.2B, and $280.0B ests; vs. street ests at $182.7B, $238.8B, and $275.2B, respectively.
The pace / growth of resumed China H20 sales is a variable (full recovery of $30B/annum+?).
We model a return to mid-70% GM% into 2HFY26 and note that we model FY26 opex at +40% y/y (vs. mid-30% y/y guide); now model FY27 and FY28 opex at +30% and +22% y/y, respectively.
Target Price Valuation: $220.00 from $185.00
Our $220 price target is ~29x P/E on our C2027E.
This compare to NVDA trading at a ~36x median NTM P/E on consensus estimates over the past three years.
We think a premium multiple for NVIDIA is warranted given its strong multi-year competitive positioning for data center growth, driven by cloud and AI, gaming, next-generation autonomous vehicles, and an expanding ecosystem of products/applications (e.g., Omniverse).
Risks include
- increased competition in the PC gaming, cloud data center markets, and high-performance computing,
- the continued development of new markets, including artificial intelligence/machine learning and autonomous driving,
- delays in product introduction due to use of third-party process technology, component availability, etc.”
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