BofA Says NVIDIA Could Be 34–50% Undervalued, Maintains $350 Price Target Despite AI Risks

BofA Says NVIDIA Could Be 34–50% Undervalued, Maintains $350 Price Target Despite AI Risks

2026/08/23 11:12:00
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NVIDIA remains at the center of the global artificial intelligence investment boom, but its rapid expansion into AI infrastructure is creating a more complicated debate around NVDA stock valuation. Bank of America analyst Vivek Arya continues to rate NVIDIA a Buy with a $350 price target, arguing that concerns about large AI financing commitments may be placing too heavy a discount on a company that continues to generate exceptional revenue, margins and cash flow. BofA’s analysis suggests NVIDIA could be trading at roughly a 34% to 50% discount on a free-cash-flow basis after accounting for risks associated with the broader AI infrastructure investment cycle.
 
The bullish case now extends beyond demand for GPUs. NVIDIA is becoming increasingly involved in the infrastructure needed to deploy those chips, including data centers, networking, power capacity and financing partnerships. That strategy could expand the market for NVIDIA systems, but it also creates new questions about contingent obligations, customer concentration and whether AI companies can generate enough economic value to support the enormous capital being invested. With NVIDIA scheduled to report fiscal Q2 2027 earnings on August 26, 2026, investors will soon get another important test of BofA’s $350 valuation thesis.
 

Why BofA Thinks NVIDIA Stock Is Still Undervalued Despite Growing AI Risks

Bank of America is maintaining a bullish view on NVIDIA stock even as Wall Street becomes more cautious about the scale and complexity of AI infrastructure financing. In its latest assessment, BofA analyst Vivek Arya kept a Buy rating and $350 NVDA price target, arguing that investors may be assigning too large a valuation penalty to NVIDIA's ecosystem investments and financial commitments. BofA's free-cash-flow-based analysis suggests the shares could be trading at roughly a 34% to 50% discount after incorporating financing risks, making the debate less about whether those risks exist and more about whether the market is pricing them too aggressively.
 

  1. Strong Free Cash Flow Keeps BofA Bullish on NVIDIA's Valuation

BofA's NVIDIA valuation case starts with the strength of the underlying business. NVIDIA reported record fiscal Q1 2027 revenue of $81.6 billion, up 85% year over year, while Data Center revenue climbed 92% to $75.2 billion. Data Center compute alone generated $60.4 billion, while networking revenue reached $14.8 billion, showing that NVIDIA is capturing spending across more of the AI infrastructure stack rather than relying only on GPU sales. Gross margins also remained near 75%, and the company returned about $20 billion to shareholders during the quarter. For BofA, that combination of rapid revenue growth, high profitability and substantial cash generation helps explain why the firm believes NVIDIA's current valuation may understate the long-term earnings power of its AI business.
 
The argument becomes more important as NVIDIA moves from selling individual accelerators toward supplying complete AI computing platforms. Blackwell deployments, networking products, CUDA software and the coming Vera Rubin generation can potentially increase the amount NVIDIA earns from each major AI infrastructure project. BofA has also pointed to strong GPU rental rates and continued scarcity of advanced computing capacity as signs that demand has not yet weakened enough to justify the full valuation discount investors appear to be applying. Still, free cash flow will remain a key metric: if NVIDIA continues converting AI demand into cash at a high rate, concerns surrounding NVIDIA’s AI ecosystem may become easier for the market to absorb.
 
Additional factors supporting NVIDIA's longer-term valuation include:
  • NVIDIA's board approved an additional $80 billion share-repurchase authorization, giving the company greater flexibility to return excess capital to shareholders.
  • The company is expanding beyond hyperscale cloud customers into AI clouds, enterprises, industrial users and sovereign AI infrastructure.
  • NVIDIA's networking business is becoming increasingly important as larger AI clusters require faster connections between thousands of GPUs.
  • A growing mix of integrated systems, networking and software could reduce NVIDIA's dependence on the economics of any single chip generation.
 

  1. NVIDIA's AI Financing Exposure Is a Real Risk, but BofA Says the Market May Be Overreacting

The biggest challenge to BofA's bullish thesis is NVIDIA's growing involvement in financing the infrastructure that ultimately creates demand for its own chips. Large AI projects increasingly require long-term commitments involving data-center operators, cloud providers, AI developers and financial institutions, creating concerns that NVIDIA could become more financially exposed to customers whose spending supports its hardware sales. BofA acknowledges that these relationships deserve scrutiny, but its valuation argument suggests investors may be assigning too much weight to worst-case outcomes rather than considering how the commitments are structured and how much risk ultimately remains with NVIDIA.
 
Several indicators could help investors judge whether the risk is increasing:
  • Customer concentration remains important because a relatively small group of hyperscalers and frontier AI companies accounts for a large portion of advanced AI spending.
  • GPU rental economics can provide an early signal of whether demand for computing capacity remains tight or supply is catching up.
  • Greater involvement from banks and infrastructure investors could reduce the amount of capital NVIDIA needs to place directly at risk.
  • The ability of AI developers to generate sustainable revenue will become increasingly important as the cost of building and operating AI infrastructure rises.
 

  1. NVIDIA's August 26 Earnings Could Test the $350 Price Target

The next major test for the BofA NVIDIA thesis arrives with NVIDIA's fiscal Q2 2027 earnings on August 26, 2026. NVIDIA has guided for approximately $91 billion in quarterly revenue, plus or minus 2%, and expects non-GAAP gross margins of about 75%. Notably, that outlook assumes no Data Center compute revenue from China, meaning investors will be able to assess the strength of NVIDIA's broader AI demand without relying on a recovery in that market. The company's latest quarter already demonstrated significant momentum, but expectations surrounding NVDA remain high, making forward guidance, margins and management's comments about demand potentially as important as the headline revenue number.
 
BofA is also expected to focus on whether NVIDIA can continue producing earnings upgrades as Blackwell deployments scale and Vera Rubin moves further into production. Stronger revenue guidance, stable margins and continued demand from hyperscalers could strengthen the argument that NVIDIA's current valuation discount is excessive. Weaker guidance or evidence of slower AI infrastructure spending, however, could make investors more cautious about applying a higher earnings multiple to the stock, particularly as broader AI stock valuation risks receive greater attention across growth markets.
 

How NVIDIA’s Massive AI Infrastructure Commitments Could Affect Its Valuation

NVIDIA’s growing involvement in AI data centers is changing the way investors may need to value the company. The business is no longer exposed only to demand for GPUs, networking equipment and software; it is also helping create the financing structures that allow customers to build enormous AI computing campuses. That strategy could strengthen NVIDIA’s long-term competitive position by accelerating deployment of its technology, but it also introduces contingent liabilities, financing exposure and capital-allocation questions that traditional semiconductor valuation models did not previously need to consider.
 

  1. The $105 Billion Ohio Guarantee Adds a New Layer to NVIDIA’s Valuation

One of the clearest examples is NVIDIA’s agreement connected to the PORTS Technology Campus in Ohio, where SB Energy is developing large-scale AI infrastructure with an OpenAI affiliate as tenant. NVIDIA’s potential obligation under the initial arrangement is capped at $105 billion, but the figure should not be treated like an immediate capital expenditure or conventional debt balance. The commitment is structured around future lease obligations and specified trigger events, meaning the amount NVIDIA ultimately pays could be substantially different from the headline maximum. That distinction matters for NVDA valuation because investors normally apply a different risk assessment to contingent guarantees than to cash already spent or debt already sitting on the balance sheet.
 
The larger issue is how markets price uncertainty around those commitments. Even if NVIDIA never has to fund the maximum amount, investors may demand a higher risk premium if off-balance-sheet guarantees become a larger part of its AI infrastructure strategy. Analysts could begin looking beyond conventional metrics such as earnings growth and semiconductor margins to estimate potential future cash calls, counterparty quality and the probability that guarantees are exercised. On the other hand, if the infrastructure operates successfully and customers continue meeting their obligations, NVIDIA could gain access to substantially more computing capacity without carrying the entire project cost itself.
 

  1. NVIDIA’s Wall Street Financing Strategy Could Keep the Model More Asset-Light

Another important development for NVIDIA’s valuation is its effort to attract institutional capital into AI infrastructure rather than financing every expansion directly. Partnerships involving major banks, private-equity firms and infrastructure investors could help mobilize hundreds of billions of dollars for data centers and computing capacity while allowing independent investors to make their own financing decisions. For NVIDIA, this model offers a way to accelerate deployment of AI systems without necessarily owning every facility or funding the majority of construction costs itself.
 
An asset-light structure could be valuable because it allows NVIDIA to preserve more capital for research, product development and strategic investments while still benefiting from higher demand for GPUs, networking and software. It could also help turn AI compute into a more established institutional asset class, making it easier for data-center operators and AI cloud providers to secure financing. The valuation benefit will depend on how much of the downside risk remains with outside investors and whether NVIDIA can avoid becoming the backstop for increasingly large projects if market conditions deteriorate.
 

  1. AI Infrastructure Could Support a Higher Multiple — or Increase NVIDIA’s Risk Discount

NVIDIA’s infrastructure push could ultimately affect its valuation in two very different ways. In a favorable scenario, easier financing allows more advanced computing capacity to be deployed, increases demand for NVIDIA systems and strengthens customer dependence on its hardware, networking and software ecosystem. Infrastructure financing may also provide NVIDIA with another competitive advantage against custom AI accelerators because customers choosing NVIDIA-based systems could gain access to a deeper network of technology partners, developers and financial institutions.
 
The opposite scenario would emerge if investors conclude that NVIDIA must commit progressively larger amounts of capital simply to maintain the pace of AI demand. In that case, the market could assign less value to future earnings because more cash may need to remain available for guarantees, customer support or infrastructure investments. NVIDIA therefore faces an unusual valuation trade-off: AI infrastructure commitments can expand its addressable market while simultaneously increasing financial complexity. How successfully the company manages that balance may become increasingly important to the multiple investors are willing to pay for NVDA.
 

Can NVIDIA Stock Reach BofA’s $350 Price Target After Its Next Earnings Report?

NVIDIA’s August 26, 2026 earnings report could become one of the most important near-term catalysts for BofA’s $350 NVDA price target, but the path to that valuation will likely depend on more than simply beating quarterly revenue expectations. NVIDIA has guided for about $91 billion in fiscal Q2 2027 revenue, plus or minus 2%, with non-GAAP gross margin expected near 75%, while BofA has reportedly modeled a stronger outcome of roughly $94 billion to $95 billion. If NVIDIA delivers results above its own guidance and pairs them with stronger forward revenue expectations, investors may become more confident that demand for AI accelerators, networking systems and full-scale data-center platforms remains durable. Attention will also shift quickly to Vera Rubin, which NVIDIA says has entered full production and could become the next major driver of AI infrastructure spending after Blackwell. For NVDA stock to move closer to BofA’s $350 price target, the market will likely want evidence that this product transition can extend the company’s growth cycle without materially weakening margins or slowing cash generation.
 
Key factors that could shape the NVIDIA stock outlook after earnings include:
  • Q3 revenue guidance near or above BofA’s estimated $107–108 billion range could support further earnings upgrades.
  • Gross margins staying close to 75% would indicate that rapid product transitions are not significantly reducing profitability.
  • Strong demand for Vera Rubin systems could strengthen expectations for continued AI infrastructure growth into 2027.
  • Continued hyperscaler capital spending would suggest that large cloud customers are still prioritizing AI computing capacity.
  • Any improvement in NVIDIA’s China opportunity could provide additional upside because current guidance excludes Data Center compute revenue from that market.
  • Slower cloud spending, weaker forward guidance or margin pressure could keep NVDA below the $350 target even if the headline quarter is strong.
 
BofA’s $350 target therefore remains a bullish valuation scenario rather than a guaranteed post-earnings outcome. The stronger case would combine a clear Q2 beat, higher forward guidance, stable profitability and convincing evidence that NVIDIA’s next product cycle is expanding demand rather than simply replacing existing Blackwell deployments.
 

Conclusion

Bank of America’s bullish NVIDIA outlook comes at a time when the company is evolving from a dominant AI chip supplier into a much broader participant in the global AI infrastructure ecosystem. BofA’s view that NVIDIA could be 34% to 50% undervalued is rooted in the company's cash-generation potential and expectations that the market may be applying too large a penalty for financing and infrastructure risks. At the same time, those risks cannot be dismissed as NVIDIA becomes connected to increasingly large data-center projects and long-term capital commitments.
 
The August 26 NVIDIA earnings report could provide an important update on whether the fundamentals continue to justify BofA’s $350 price target. Revenue growth, forward guidance, gross margins, Vera Rubin adoption and hyperscaler spending will help determine whether NVIDIA can sustain the earnings expansion required to support a higher valuation. For crypto investors following the same technology theme, AI and Big Data crypto markets offer a separate view of how artificial-intelligence narratives are developing across digital assets, although those markets carry different risks and should not be treated as a direct proxy for NVDA. Investors should therefore view the $350 target as one possible outcome based on continued execution rather than a certainty, with both AI demand and the financial structure supporting that demand likely to remain central to the NVDA stock outlook.
 

FAQs

How important is Vera Rubin to NVIDIA’s future growth?

Vera Rubin is important because it represents NVIDIA’s next major AI computing platform after Blackwell. Strong adoption could extend the company’s product cycle, support larger AI clusters and increase demand for related networking and system components. Investors will likely watch deployment timing and customer adoption closely as the platform scales.

Could custom AI chips threaten NVIDIA’s market share?

Custom accelerators developed by major cloud companies could reduce NVIDIA’s share of some workloads over time, particularly where customers want lower costs or specialized performance. However, NVIDIA competes through more than GPUs alone, including CUDA software, networking, developer tools and integrated systems, which can make switching platforms more complicated for customers.

Why does hyperscaler spending matter so much for NVIDIA stock?

Large cloud providers account for a significant share of global AI infrastructure investment, making their capital-expenditure plans an important indicator of future NVIDIA demand. If companies continue increasing spending on AI data centers, NVIDIA could benefit from additional GPU, networking and system sales. A broad slowdown in cloud investment would create the opposite risk.

How could interest rates affect NVIDIA’s AI infrastructure growth?

Higher interest rates can make large data-center projects more expensive to finance, especially for companies relying on debt or external investment. This could slow some AI infrastructure projects even if demand for computing remains strong. Lower financing costs, by contrast, can make it easier for developers and infrastructure investors to fund new capacity.

What should investors watch besides NVIDIA’s quarterly revenue?

Revenue is important, but investors may also want to monitor forward guidance, gross margins, operating cash flow, product availability, customer concentration and capital spending trends. Together, these indicators can provide a clearer picture of whether NVIDIA’s current growth is sustainable beyond a single quarter.
 

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