5-star analyst sets jaw-dropping Nvidia stock price target before earnings

Nvidia (NVDA) stock closed the May 15 trading session 4.42% down at $225.32, according to Yahoo Finance. However, most semiconductor stocks fell on Friday.

The cause of this sell-off was President Donald Trump’s meeting with Chinese leader Xi Jinping, which ended without major chip deals, as reported by the Wall Street Journal.

Another factor may have been a strong warning from UBS analysts about semiconductor stocks and the Magnificent 7, reported Proactive.

In addition to these two factors, Nvidia’s Q1 fiscal year 2027 earnings are set to be released on May 20. It has become a common pattern for Nvidia’s stock to experience volatility near earnings, despite consistently beating the outlook.

Nvidia CEO Jensen Huangexplained this phenomenon at the all-hands meeting after the Q3 fiscal 2026 earnings. “If we delivered a bad quarter, it is evidence there’s an AI bubble. If we delivered a great quarter, we are fueling the AI bubble.”

The one-day drop is likely just a hiccup for the ongoing rally. The stock is up about 0.3%, trading at $226.0, according to Yahoo Finance at the time of writing, Monday morning, May 18.

The semiconductor stocks started their rally at the end of March. Many news items contributed to it, including hyperscalers increasing their capital expenditure plans, Bank of America revising its server CPU sales forecasts, and Intel’s Q1 earnings boosting confidence in the semiconductor sector.

As long as the hyperscalers continue to invest heavily in AI buildout, the rally is likely to continue.

Keybanc raised Nvidia stock price target.

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Nvidia’s focus on networking is growing

Nvidia announced on March 31 that it has invested $2 billion into Marvell (MRVL) and entered into a strategic partnership with the company.

The deal is one of three Nvidia’s recent investments into companies with expertise in silicon photonics. The previous two were investments of $2 billion in Lumentum Holdings (LITE) and $2 billion in Coherent Corp. (COHR).

The reason silicon photonics is important is that, unlike traditional optical modules used in networking, it uses common-wavelength lasers, which are less expensive and easier to manufacture.

Here is what Hock Tan, Broadcom (AVGO) President and CEO, said during the Q4 earnings call about Silicon photonics:

“And of course, when you can’t do it even in copper, then you’re right. You go to silicon photonics, and it will happen.”

What Tan is saying here is that once copper transceivers can’t be improved further, the switch from copper wires to lasers will happen. It turns out that Advanced Micro Devices (AMD) also thinks Nvidia’s investment in Marvell was a smart move, as the company also invested in Marvell.

Related: Cathie Wood sells $40.6 million of popular semiconductor stock

It is also very interesting to note that Marvell is also a competitor to both Nvidia and AMD, with its custom AI accelerators. This signals the shift towards the growing importance of networking technology for the AI data center build-out.

We can also see this change in Nvidia’s 10-K form for fiscal year 2026. Its networking revenue totaled $31.4 billion. That was a pretty big jump from $13 billion in 2025.

Nvidia is increasing the power and flexibility of its AI factories

Nvidia unveiled the Groq 3 LPX accelerator at its GPU Technology Conference (GTC) in March. This custom accelerator is a special chip built just for inference, designed to meet the low-latency, large-context demands of agentic systems.

Ensuring that the company’s offerings include powerful inference racks was very important for strengthening the company’s AI factory strategy.

The key selling point for AI factories is sovereignty. Data ownership, privacy, and model fine-tuning are among the reasons any company or organization that can afford it would want a sovereign AI. The AI factory strategy also means that, in the long run, Nvidia won’t depend on companies working on frontier AI models.

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This is because, to achieve full AI sovereignty, the customer needs access to a high-quality open model, and Nvidia addresses this with its line of Nemotron AI models. On April 28, Nvidia launched Nemotron 3 Nano Omni, an open, multimodal model with vision, speech, and language capabilities in a single system.

The company said this allows AI agents to deliver faster, smarter responses with advanced reasoning across video, audio, image, and text.

As earnings are near, analysts are resetting their Nvidia forecasts. Goldman Sachs recently reset its EPS forecast, and TD Cowen reset its Nvidia stock price target.

Keybanc raises Nvidia stock price target

Keybanc analyst John Vinh also updated his opinion on Nvidia stock ahead of earnings, according to TipRanks.

Vinh is one of the analysts with the best track records out there. His TipRanks profile shows he ranks 68th out of 12,237 Wall Street analysts, with a 64% success rate and an average return of 29.8%.

The analyst said he believes Blackwell GPU shipments will rise by 150,000 to 200,000 quarter over quarter, translating into sequential revenue growth of $5 billion to $7 billion.

He raised his fiscal Q1 and Q2 revenue estimates from $78.1 billion and $84.9 billion to $80.8 billion and $89.5 billion, compared with consensus at $78.8 billion and $86.9 billion.

As a reminder, here is Nvidia’s guidance for Q1 2027:Revenue of $78.0 billion, plus or minus 2%.GAAP gross margin of 74.9%, plus or minus 50 basis pointsGAAP operating expenses of approximately $7.7 billion
Source: Nvidia

Vinh reiterated an overweight (buy) rating for Nvidia stock and raised the price target to $300 from $275. Vinh’s price target implies an upside of 32.74% from the current trading price.

In a research note from May 13, shared with me, Bank of America analyst Vivek Arya and his team reset the stock price target for AMD, which is one of Nvidia’s competitors, and updated their opinion on Nvidia stock. He ranks as 94th, with a 64% success rate and an average return of 27.0%.

Arya reiterated a buy rating for Nvidia stock and raised the price target to $320 from $300, based on a 28 multiple of his estimate for price-to-earnings ratio excluding cash for calendar year 2027, which is within Nvidia’s historical forward year P/E range of 25 to 56.

Arya’s price target implies an even bigger upside of 41.59% from the current trading price.

The downside risks for investing in Nvidia include hyperscalers slowing overall AI spending, the company losing market share in AI accelerators, and supply constraints.

The author holds no position in any of the stocks mentioned at the time of writing.

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