Track market-moving stories before they get noisy

Following the steep correction in June, Nvidia (NASDAQ: NVDA) stock price is set to remain flat by July 31, 2026, per the prediction made on July 1 by the Finbold AI Agent.

Specifically, after using multiple technical analysis (TA) tools, including the relative strength index (RSI), moving averages (MA), and stochastic oscillators, the predictive artificial intelligence (AI) tool estimated that NVDA shares would fall 0.16% to $199.55 from the press-time extended-session price of $199.87.

Finbold AI sets Nvidia stock price target for July 31, 2026. Source: Finbold Notably, the average prediction that Nvidia’s stock price will remain effectively flat by July 31 is the result of a sharp divergence in forecasts among the five models included in the system.

Indeed, Anthropic’s Claude Opus 4.6 proved significantly more bullish than the overall target, estimating NVDA would climb 4.32% to $208.50.

Claude AI sets Nvidia stock price target for July 31, 2026. Source: Finbold On the other end of the spectrum, Google’s (NASDAQ: GOOGL) Gemini 3 Flash was, by far, the most bearish as it forecasted a further 4.21% drop to $191.45.

Google AI sets Nvidia stock price target for July 31, 2026. Source: Finbold xAI’s Grok 4.1, for its part, was closer to the analysis made by Alphabet’s AI given its $192.50 target after a 3.69% correction. OpenAI’s flagship platform, ChatGPT-5.2, was closer to Claude with a 2.72% predicted rally to $205.30.

Lastly, DeepSeek was remarkably close to the average with a prediction that Nvidia stock will remain effectively flat – or, more precisely, that it will rise 0.07% to $200.

Nvidia stock price chart Meanwhile, June proved to be a red month for NVDA shares, as it led to a 10.82% stock price drop from $224.36 at the June 1 close to $200.09 on June 30, and to an overall $588 billion market capitalization wipe.

Nvidia stock price one-month chart. Source: Google The downturn appears to have been driven by a destabilization of the AI boom narrative triggered by the rising debate on the technology’s costs and benefits, but also a rotation to more up-and-coming sectors like memory and even into smaller semiconductor companies like AMD (NASDAQ: AMD) and Intel (NASDAQ: INTC).

Still, despite the decline, Nvidia remains significantly above the March lows and is still in the green in 2026, with the year-to-date (YTD) chart showing an overall 5.95% rally.

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Nvidia (NVDA +2.66%) may have once made many millionaires. If you had invested $1,000 in the company in its early days of trading and held on, today you would have more than $5 million. Most of the gains happened over the past few years, as the artificial intelligence (AI) boom took shape -- Nvidia makes the key chips that power crucial AI tasks, like the training of AI models, and has built out expertise in a wide range of related products.

All of this supercharged earnings growth, sending it to record levels, and as a result, investors rushed to get in on the stock. And those who recognized Nvidia's potential in its earlier days scored a gigantic win.

Now, however, after Nvidia's incredible run, climbing more than 800% over just the past five years, you may wonder if the stock still is a millionaire-maker. Let's find out.

Image source: Getty Images.

Nvidia's growth story We'll start by talking about Nvidia's story so far. The chip designer wasn't always an AI specialist. After all, Nvidia was founded more than 30 years ago, well before the days of AI. The company's graphics processing units (GPUs) then mainly served the video games market, but in more recent years, Nvidia broadened the usage of its chips by creating the parallel computing platform CUDA. That eventually opened the door to use in the AI market -- and Nvidia, seeing the opportunity, got involved early, designing GPUs specifically to suit the needs of AI customers.

All of this worked out well for Nvidia, as we can see through its earnings reports in recent years. The company reported more than $215 billion in revenue in the latest full year and continued to see earnings roar higher in the latest quarter. In that period, revenue rose 85% to $81 billion, and net income advanced more than 200% to $58 billion.

The stock price has soared throughout most of the AI boom, but in recent months, Nvidia stock hasn't been much of a performer.

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This hasn't been due to any bad news in the AI market or news concerning Nvidia in particular. Instead, general worries have weighed on AI stocks. Last year, investors questioned the sustainability of their high valuations. Valuation has come down quite a bit since, but another concern has lingered: Some investors question whether the future AI revenue opportunity justifies the current levels of AI spending. Even though companies from Nvidia to cloud service providers like Microsoft and Amazon have spoken of soaring AI demand, and AI revenue is climbing at these and other companies, the concern has periodically weighed on Nvidia and other AI players. Particularly, stocks that have skyrocketed in recent years.

Starting from lower price and market cap levels Now, let's return to our question: Against this backdrop and at this point in the AI story, is Nvidia still a millionaire-maker stock? It's important to remember that it was easier for Nvidia to generate millions when the stock price and market value started out from much lower levels.

NVDA data by YCharts

Today, with Nvidia's market cap at more than $4.5 trillion, it's difficult for the company to double or triple in size. This makes enormous gains in a short period of time much more difficult.

So, with a $1,000 investment in Nvidia, it seems impossible to reach millionaire status. Of course, with an enormous investment in the company, you could potentially become a millionaire -- but it's very risky to make one big investment and count on that stock to produce wealth.

Instead, it's a safer idea to invest in a broad range of quality stocks. And you're likely to be more successful this way, too. Using this strategy, Nvidia could help you along the road to wealth, as the stock still has room to run during the AI boom and beyond. Nvidia holds the leading position in the GPU market, and this should continue thanks to the company's focus on innovation. Meanwhile, the stock, trading at 21x forward earnings estimates, is dirt cheap right now, making it an excellent buy.

So, even though Nvidia may not be a millionaire-maker on its own, it still could offer your portfolio a huge lift over time.

Nvidia (NVDA +2.66%) has been the hottest stock on Wall Street in recent memory. Over the past five years, the company has delivered incredible returns. But how incredible, exactly? Read on to find out how much a $1,000 investment in Nvidia would be worth today.

Image source: The Motley Fool.

The party may not be over Nvidia has posted a compound annual growth rate (CAGR) of 59.49% since 2021, as of this writing. That means if you had started with $1,000 five years ago, you'd now have $10,319.71. For comparison, the S&P 500's CAGR over the same period was 13.06%, so it would have turned an initial $1,000 investment into $1,847.33.

NVDA Total Return Level data by YCharts

That's a massive difference. Of course, investors are more interested in what will happen next than in what has happened in the past. Can Nvidia still deliver above-average returns? Several data points suggest so, despite the stock declining in recent weeks. Here's one thing to consider: Nvidia remains the undisputed leader in the GPU (Graphics Processing Unit) market as hyperscalers spend massive sums on artificial intelligence (AI) infrastructure, and they may continue doing so for the foreseeable future.

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Meanwhile, Nvidia's shares are surprisingly cheap relative to the company's growth potential, perhaps because some investors think the AI tailwind will fade pretty soon. The tech leader is trading at 22.2x forward earnings, compared with an average of 22.4x for information technology stocks. A company of Nvidia's stature, which leads its industry, boasts a wide moat due to switching costs and is still tapping into a fast-growing market, in my view, deserves a healthy premium. Anything less suggests the stock is trading at a steep discount. That's why investors should rush to buy Nvidia's shares. It may not perform as well through 2031 as it has over the past five years, but it could still deliver solid returns.

DeepSeek released DSpark last week. The market noticed the speed numbers and moved on. What the speed numbers actually signal is more important than the benchmark: A Chinese AI lab keeps finding ways to make inference faster using software and open weights, at no cost to anyone who wants to use it.

Nvidia (NVDA +2.00%), meanwhile, is ramping a specialized decode rack called the Groq 3 LPX that requires a separate purchase decision on top of the GPU platform customers already depend on. The question the market is not asking is whether that second check gets written at scale, or whether DSpark and the architectural innovations underneath it are quietly making the answer no.

Nvidia just posted the biggest quarter in semiconductor history. Revenue of $81.6 billion. Data Center revenue of $75.2 billion. GAAP gross margin of 74.9 percent. The established GPU business is not in question. What is in question is the incremental layer Nvidia is now trying to monetize on top of it.

The New Bet Nvidia Is Making The investment case has quietly shifted layers. Selling GPUs to hyperscalers is the established business. The new ambition is to sell a specialized decode rack alongside those GPUs, positioned as a required upgrade for the most demanding agentic AI workloads.

That rack is the Groq 3 LPX, built around 256 Groq LPU accelerators. Each LPU carries 500MB of on-chip SRAM running at 150 terabytes per second of bandwidth, roughly seven times the memory bandwidth of a Rubin GPU. Paired with the Vera Rubin NVL72 GPU system, Nvidia claims the combination delivers up to 35 times higher inference throughput per megawatt for trillion-parameter models. Vera Rubin is now in full production. LPX is shipping to early customers in the second half of 2026.

The pitch is compelling. The risk is that it requires a separate purchase decision from customers who have already committed to Rubin GPUs. DSpark arrived and made that decision harder.

Why Decode Is the Profit Pool Nvidia Wants to Own LLM inference splits into two distinct phases. Prefill processes the input prompt and generates the initial memory state. Decode generates output tokens one step at a time, using that memory state under sustained pressure from active users, long outputs, and large context windows.

Decode is slower, more memory-intensive, and harder to scale efficiently. The memory structure at the center of this pressure is the KV cache, which grows with context length and must be read repeatedly for every generated token. For long-context agentic workloads, the KV cache can consume the majority of available GPU memory.

This is the bottleneck LPX is designed to monetize. If decode remains the dominant constraint on inference quality and cost, LPX becomes a necessary part of any serious agentic deployment.

Image source: Getty Images.

Disaggregation Is an Industry Bet, Not Just an Nvidia Bet This is important context for evaluating LPX. The case for separating prefill and decode onto specialized hardware is not Nvidia's alone. It is the conclusion the entire industry has reached simultaneously, which validates the underlying thesis but complicates the investment case for LPX specifically.

In March 2026, AWS and Cerebras announced a multiyear collaboration that puts Cerebras CS-3 wafer-scale engines inside AWS data centers, pairing them with Trainium 3 for prefill and Cerebras CS-3 for decode, connected via Amazon's Elastic Fabric Adapter networking. The architecture is identical in logic to Nvidia's LPX play: prefill and decode require different silicon, and serving them on the same hardware leaves performance on the table. AWS described the result as delivering inference an order of magnitude faster than existing GPU-only solutions. The service is launching through Amazon Bedrock in the second half of 2026, on the same timeline as LPX.

The bear case sharpens here. If every major cloud provider reaches the same architectural conclusion and builds their own answer to it, Nvidia's LPX attach rate becomes a question of whether customers who buy Rubin GPUs also buy LPX as a second rack, or whether they route their most latency-sensitive decode workloads to a hyperscaler-native alternative instead.

DSpark Is the Latest Move in a Longer Pattern DeepSeek released DSpark on June 27, 2026. It is not a new model. It is a speculative decoding module attached to DeepSeek-V4-Flash and V4-Pro, now running live in production.

The mechanism is worth understanding because it directly attacks the decode bottleneck. A smaller draft model proposes multiple tokens at once. The large target model verifies them in parallel. When the draft is right, multiple tokens are accepted in a single step. Fewer full decode passes are required per output. The memory and compute burden per token falls.

DeepSeek reports per-user generation speed improving 60% to 85% on V4-Flash and 57% to 78% on V4-Pro over the prior baseline. Throughput at a fixed service level improved 51%. These numbers come from DeepSeek's own benchmarking and have not been independently verified as of this writing. What is verifiable: DSpark is live in production, open-sourced under the MIT license, and the companion DeepSpec training framework already extends to Qwen and Gemma model families. The efficiency gains are not staying inside DeepSeek's own ecosystem.

One nuance worth stating plainly. Nvidia's own LPX architecture supports speculative decoding. Dynamo is designed to orchestrate draft-and-verify workflows across the GPU-LPU combination. DSpark and LPX are not simply in opposition. The more pointed bear case is that DSpark running on general Rubin GPUs alone, without LPX attached, delivers enough inference efficiency that the second rack becomes optional for most workloads.

DSpark is also not the first move in this pattern. DeepSeek has been quietly shrinking the memory problem that decode hardware is designed to solve. Its MLA architecture, carried through every model generation since V2, stores a compressed representation of past context instead of the full memory state a standard model would keep. The practical result: DeepSeek-V4-Pro needs roughly 10% of the memory that V3.2 required for million-token conversations. Less memory pressure means less urgency for hardware whose main selling point is handling that pressure. DeepSeek is reducing the problem inside the model before the hardware ever sees it.

The causal chain for investors is this. Decode is a memory and latency problem. LPX is a hardware solution to that problem. DSpark and MLA are software solutions to the same problem. They are open, free, and already in production.

The Trade-Off the Market Is Not Pricing This is not a story about Nvidia losing the AI infrastructure market. Hyperscalers have already secured Vera Rubin allocations. Nvidia CEO Jensen Huang confirmed more than $1 trillion in combined Blackwell and Rubin purchase orders through 2027. That figure covers GPU systems and associated networking. It does not include LPX racks, Vera CPU systems, or storage, all of which are incremental.

The trade-off is specific. LPX must deliver enough guaranteed latency and throughput improvement over general Rubin GPUs running DSpark-style inference to justify a separate rack purchase, and to do so while competing against hyperscaler-native decode alternatives that carry none of LPX's integration friction. That hurdle just got higher on two fronts simultaneously: software efficiency is rising and the competitive field for specialized decode hardware is widening.

Geopolitical restrictions protect some hardware supply but not the ideas. DSpark is MIT-licensed and already running on model families beyond DeepSeek's own.

Token volume can rise while hardware intensity per token falls. That is the asymmetry that the market is not pricing.

What the Financial Exposure Actually Looks Like The forward numbers require one specific question. Full-year fiscal 2027 Data Center revenue consensus sits near $343 billion, per S&P Global Visible Alpha. That implies continued sequential growth through the Vera Rubin ramp. The consensus Data Center gross margin for fiscal 2027 is projected at 76.3%, slightly below fiscal 2024 and 2025 levels.

The LPX bear case does not threaten GPU demand. It threatens the incremental attach: LPX racks, disaggregated serving infrastructure, and the premium networking and storage configurations justified by worst-case decode loads. If LPX lands narrowly among the highest-concurrency, longest-context deployments rather than broadly across agentic workloads, the incremental revenue layer implied by the consensus trajectory is harder to underwrite at current multiples.

What Would Make the Bear Case Wrong This is what would make the bear case wrong: LPX becomes a required component for agentic deployments, not a premium option. Cloud providers report service-level improvements only achievable with LPX attached to Rubin and disclose this publicly. Nvidia reports LPX rack demand separately from general Rubin GPU demand in upcoming earnings calls, with numbers large enough to matter.

The AWS-Cerebras disaggregation stack proves difficult to scale or faces latency limitations from the EFA interconnect between Trainium and CS-3, pushing customers toward the tighter GPU-LPU co-design of LPX. DSpark-style speculative decoding shows weak acceptance rates in production reasoning and complex agentic workflows, where output is less predictable. KV compression architectures prove difficult to extend beyond DeepSeek's model family. The CUDA compatibility gap closes with the LP35 generation, removing a meaningful adoption friction point.

What Would Confirm the Bear Case Here's what would make the bear case right: Nvidia discusses Vera Rubin demand broadly in upcoming earnings without evidence of LPX attach rates. Hyperscalers deploy DSpark-style speculative decoding and MLA-derived attention at scale, with infrastructure reporting showing lower hardware intensity per token. The AWS-Cerebras Bedrock launch gains rapid enterprise adoption, demonstrating that customers route latency-sensitive decode workloads to hyperscaler-native alternatives rather than LPX. Token prices fall faster than Nvidia's hardware cost reductions, compressing customer payback periods for LPX investment. DeepSpec-style efficiency gains appear in Qwen, Gemma, and other major open model families, making this about architectural diffusion rather than one Chinese vendor.

Judge the Next Nvidia Inference Cycle by LPX Attach, Not Token Volume Nvidia's GPU platform is not in question. The Blackwell ramp was real. The Vera Rubin orders are real. The agentic AI inflection Jensen Huang describes is real.

What is in question is whether the inference specialization layer gets purchased at the scale the consensus numbers imply. The bear case is not that inference stops growing. It is that DeepSeek and its open-source successors keep compounding software efficiency, that hyperscalers build their own decode alternatives, and that all of this happens at the exact moment Nvidia is trying to monetize a hardware solution to the same problem.

The decisive metric over the next two to three quarters is not Data Center revenue. It is whether Nvidia can show that Vera Rubin customers attach LPX because neither general Rubin GPUs running DSpark-style inference nor hyperscaler-native disaggregation alternatives can meet their latency targets at scale. That signal will either underwrite the consensus or put it in doubt. Everything else in the Nvidia story is already priced.

NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) was expected to lead semiconductors higher in 2026. Instead, it has watched the rest of the group sprint away. CEO Jensen Huang calls the current moment “the buildout of AI factories, the largest infrastructure expansion in human history”, and the financials back him up. Nvidia’s Q1 2027 data Center revenue hit $75.246 billion, up 92% year over year. Yet the stock is up just 6.2% on the year. Can NVIDIA shares hit $300 by year-end 2026?

Why NVIDIA Shares Are Stuck While Semis Rip The divergence is stark. The VanEck Semiconductor ETF (SMH) is up 75.49% YTD and 127.69% over one year. NVIDIA is up 29.2% over one year and down 11% over the past month.

Metric NVDA SMH YTD +6.2% +75.49% 1-Month -11% +5.52% 1-Year +29.2% +127.69% Three headwinds weigh on shares. First, Q2 guidance of $91.0 billion ± 2% explicitly excludes Data Center compute revenue from China. Second, a beta of 2.202 amplifies AI-bubble jitters.  Investors are rotating into memory, equipment, and optical names that screen cheaper. Third, a beta of 2.202 amplifies every AI-bubble jitter, so this stock takes the hardest hit when risk sentiment wobbles.

The Consensus Is Bullish. Our Model Says Be Patient Wall Street targets $301.62 with 10 strong buy, 48 buy, 2 hold, and 1 sell rating. Our base case is more measured at $248.09 with an optimistic scenario of $259.31, carrying 90% confidence. Our model rates NVIDIA positively but sits well below the Street.

Here is where we push back on our own conservatism. 95% of analysts are bullish, and earnings growth was a +0.03 contributor to our 247 Factor even though Q1 net income grew 210.63% YoY. That gap between actual earnings velocity and modeled contribution is slack that can close fast.

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The Path to $300 Per Share Reaching $300 from today’s price of $198.63 requires a gain of 51.0%. With forward EPS of $8.97, $300 implies a forward P/E of 38x. Our base case of $248.09 already implies 34x, meaning the bold target needs roughly 3.6x additional multiple expansion.

Five catalysts could deliver it:

Forward estimates keep climbing. Yahoo Finance consensus has fiscal-2028 EPS at $12.76, up from $11.11 just 90 days ago, with fiscal-2027 EPS rising to $8.97 from $8.30. Estimates up, price flat. Forward multiples compress quietly. Vera Rubin execution. Huang has called “Grace Blackwell with NVLink” the “king of inference” with Vera Rubin, which is behind agentic AI and reasoning models, extending that lead. Robotics and physical AI. Per the South China Morning Post (June 30, 2026), NVIDIA is recruiting for more than a dozen roles across Beijing, Shanghai and Shenzhen spanning embodied intelligence, simulation, and Project GR00T. Sovereign AI. NVIDIA’s June 29, 2026 blog announced Palantir’s new engine using NVIDIA Nemotron models in air-gapped U.S. government deployments. China access and new CPUs. H200 licensing and Arm-based CPU launches are reported swing factors for 2H. Primary risk: tighter China export rules or any Vera Rubin slip would freeze the multiple where it sits.

Where NVIDIA Trades Today vs Its Earnings Power At $198.63 against forward EPS of $8.97, NVIDIA trades around 25x forward earnings. Alpha Vantage pegs forward P/E at 22. Either way, that is a modest multiple for a company growing revenue 85.2% YoY at 75.0% non-GAAP gross margins. Shares sit between a 52-week range of $152.77 and $236.26, and the 10-year return is +16,943.1%. The valuation case writes itself if earnings keep accelerating.

Is $300 Realistic? $300 is a stretch from $198.63, implying a 51.0% gain in six months. For it to work, forward estimates need to keep climbing, Vera Rubin needs a clean ramp, and the China headwind needs to soften. A regulatory clampdown on AI chip exports would derail it. With the Street already at $301.62 and EPS trends pointing up, the math is more achievable than recent price action suggests. Returns at this level shouldn’t be expected every year, but the blueprint for NVIDIA reaching $300 in 2026 is clearly within grasp.

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Nvidia (NVDA +1.44%) is capping off another successful quarter of trading. The global leader in artificial intelligence (AI) is trading 12% higher heading into the final trading day of the calendar quarter.

But June has been a bust. Nvidia is trading 8% lower in this otherwise resilient month for the markets. Market leadership has shifted from the initial AI leaders to beneficiaries like memory and data storage manufacturers. The upticks there have been driven by demand outstripping supply, resulting in surging prices and thick margins for a historically cyclical industry.

Could this also be an opportunity for existing or potential Nvidia investors? Let's go over some of the reasons why the stock with the largest market cap can bounce back in July.

Image source: Getty Images.

1. Nvidia doesn't lose the headline war forever Don't let June's slide dissuade you. Nvidia stock has continued to be a winner over longer stretches of time. The 5% year-to-date return is trailing the market, but zoom out, and you'll see the stock is up 24% over the past year, more than quadrupling over the three years and almost a 10-bagger over the past five years.

Some of the June headlines are unflattering but potentially misleading:

Other "Magnificent Seven" stocks are starting to sell their own AI chips. Nvidia had a massive $25 billion bond sale this month, its first debt offering in five years. Despite several head fakes over the past year, Chinese restrictions for AI remain painfully in place. Nvidia seems to be fighting upstream in the headwind headline war. It won't always be that way. Remember when Nvidia stock was rattled in early 2025 by reports that China's DeepSeek was achieving major AI advancements on older, less powerful chips? That ultimately didn't slow Nvidia down.

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2. This is still a great growth stock Nvidia doesn't report its financials again until late August. It operates on a different fiscal calendar than many tech titans, which report in the latter half of July.

It's still delivering strong results. Revenue soared 85% in its latest financial report. Margins continue to improve, with adjusted earnings blasting 139% higher.

Nvidia is doing this even amid a sharp reversal in its sales in China, rising competition, and percolating supply chain constraints. The company continues to deliver market-thumping results on a stunning 55.7% adjusted net margin. History is a long game, but Nvidia continues to win the quarterly chapters.

3. The stock is even cheaper than you think Nvidia stock is moving lower in June. Expectations are going the other way. Analysts see Nvidia earning $8.97 per share this fiscal year and $12.76 per share in the new fiscal 2028 year, which starts in late January of next year.

A month ago, those per-share adjusted net income targets stood at $8.95 and $12.66, respectively. Three months ago, those adjusted per-share earnings estimates stood at $8.30 and $11.11, respectively.

As an investor, it's important to recognize moments when market sentiment diverges from fundamentals. If the future is getting cloudy or showing signs of deterioration, that's a fair time to get cautious. But when the outlook is only getting better, that's often a buying opportunity.

How expensive do you think Nvidia is these days? I'll spare you the suspense of overestimating the numbers. Based on Monday's close of $194.97, the world's most valuable company by market cap is trading for less than 22 times this year's earnings. Step up to the new fiscal year that starts in seven months, and Nvidia is fetching just 15 times Wall Street's profit target for that year.

There's no denying that Nvidia's competitors are getting smarter, and that institutional rotation has shifted from the wearer of the AI coat to the coattails. Nvidia is still trading at a discount to many tech players that are growing more slowly and have yet to prove their AI resilience. Don't let the rough June get in the way of Nvidia's potential to heat up this summer.

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Stock to Watch: Nvidia (NVDA - Free Report) Santa Clara, CA-based NVIDIA Corporation is the worldwide leader in visual computing technologies and the inventor of the graphics processing unit, or GPU. Over the years, the company’s focus has evolved from PC graphics to artificial intelligence (AI) based solutions that now support high-performance computing (HPC), gaming and virtual reality (VR) platforms.

NVDA is a #3 (Hold) on the Zacks Rank, with a VGM Score of A.

Additionally, the company could be a top pick for growth investors. NVDA has a Growth Style Score of A, forecasting year-over-year earnings growth of 88.7% for the current fiscal year.

16 analysts revised their earnings estimate upwards in the last 60 days for fiscal 2027. The Zacks Consensus Estimate has increased $0.94 to $9.00 per share. NVDA boasts an average earnings surprise of +5.5%.

With a solid Zacks Rank and top-tier Growth and VGM Style Scores, NVDA should be on investors' short list.

Nvidia NVDA stock rose on Tuesday. Shares of Nvidia were up 1.5% at $197.96 in early trading.

Despite the gain, Nvidia has significantly underperformed the broader semiconductor sector.

The stock is up roughly 5% year to date, compared with a 94% gain for the PHLX Semiconductor Index.

The muted performance marks a sharp contrast to Nvidia's dominant run over the past several years and would represent the stock's weakest first-half showing since 2022.

Investor attention is increasingly focused on whether Nvidia's upcoming Vera Rubin platform can restore the company's position as the undisputed leader in AI infrastructure.

The central challenge facing Nvidia is no longer limited to competition from rival graphics processor makers.

While Advanced Micro Devices remains a key competitor, the market has expanded to include custom chip developers and companies focused on central processing units, including Intel.

As artificial intelligence spending accelerates, major technology companies are increasingly distributing infrastructure budgets across a wider range of suppliers rather than concentrating purchases with a single vendor.

The key question for investors is whether Nvidia's next-generation hardware can establish a sufficiently large performance advantage to justify continued dominance in AI deployments.

Nvidia's relative underperformance has become one of the more notable developments in the semiconductor sector this year.

After several years of outsized gains, many investors appear to have taken profits and rotated into other areas of the AI supply chain, including memory chipmakers and emerging AI infrastructure companies.

Intel shares have climbed approximately 250% this year, while Advanced Micro Devices has gained about 152%.

The iShares Semiconductor ETF has advanced roughly 102% over the same period.

The shift suggests investors increasingly believe much of Nvidia's expected growth has already been reflected in the stock price, even as demand for advanced AI hardware remains strong.

Sentiment has also been weighed down by concerns over export restrictions affecting sales to China and broader questions about how long Nvidia can sustain the extraordinary growth rates it has delivered in recent years.

At the same time, Nvidia is expanding its focus beyond traditional AI infrastructure and into robotics and physical AI.

The company is ramping up hiring for its robotics operations in China, advertising more than a dozen positions across Beijing, Shanghai, and Shenzhen, according to a recruitment post published on its official WeChat account.

The openings cover embodied intelligence, simulation, implementation, and solutions.

Nvidia said the robotics team aims to build a "leading robotics platform and ecosystem to help developers and companies create autonomous machines," with the goal of accelerating the deployment of robots from research environments into real-world applications.

The recruitment drive highlights Nvidia's growing emphasis on physical AI, which combines artificial intelligence models with robotics systems that can perceive, reason, and interact with the physical world.

According to the job descriptions, employees will work on technologies including the Project GR00T humanoid robot foundation model, the Cosmos physical simulation world model, and Nvidia's GPU-accelerated computing platforms.

Magnificent 7 stocks have retreated sharply this year and erased over $2.3 trillion in value. The closely-watched Roundhill Magnificent 7 ETF (MAGS) dropped to $60.80 from the year-to-date high of $71.17. 

Most companies in the group have dived in the past few months. Nvidia, the world's largest company, has dropped by nearly 20% from its year-to-date high.

Similarly, Microsoft stock has dived by 33%, while Meta Platforms, Amazon, and Tesla have fallen by 30%, 14%, and 16%, respectively from their highest levels this year. Apple has also dropped modestly from its year-to-date high, down from $317 to $280 today.

One possible reason behind the ongoing Magnificent 7 stocks retreat is that investors are taking profit after their surge. At its peak this year, Apple was up by over 150% from its lowest level in 2023. Nvidia was up by 43% from the lowest level last year. 

Most notably, these stocks are retreating because of the sector rotation towards companies in the memory industry. A closer look at data shows that memory companies are among the top gainers this year. This includes companies like Micron, Sandisk, Western Digital, and Seagate. Most recently, the Roundhill Memory ETF (DRAM) has accumulated over $24 billion in assets since its launch in April.

The companies have done well amid the ongoing supply shortage that has pushed their prices to the highest level on record. As a result, hyperscalers, who are their biggest clients, are having to spend billions of dollars more. 

For example, the top hyperscalers are planning to spend over $750 billion in capital expenditures this year, much higher than what they spent last year. This surge is driven by both new data center launches and soaring memory prices.

Just last week, Apple made headlines last week when it said that it would hike prices of its MacBooks because of higher prices. It is also considering hiking iPhone prices. 

Some Magnificent 7 stocks are also falling amid fears of return on investment (RoI) as they boost their data center spending. The most affected companies in this are the top hyperscalers like Microsoft, Meta, and Google.

At the same time, they have now started raising capital in highly dilutive ways to fund their ambitions. For example, Google recently raised over $80 billion in a combination of debt and equity, diluting its shareholders. 

Meta Platforms is considering such a move, while Nvidia recently raised over $25 billion in debt. Tesla has already warned that it will not generate positive cash flows this year because of its Terafab 

Therefore, some analysts are worried about whether they will achieve the return on investment any time soon. 

Still, on the positive side, these companies have now become bargains. For example, data shows that Nvidia is trading at a forward price-to-earnings (PE) multiple of 22, slightly lower than the S&P 500 Index’s 23. Meta Platform’s forward PE ratio has dropped to 16, while Google’s multiple has fallen to 23. 

Therefore, since these are some of the most profitable companies in the world, there is a likelihood that investors will rotate to these companies, potentially after the next earnings season.

I keep buying NVIDIA (NASDAQ:NVDA | NVDA Price Prediction), and the receipts make it hard to stop. Every paycheck, every dip, every quarter that prints another set of numbers most companies will never see, I add. This is the position I size up when I should be diversifying away from it, and I want to explain why with the data.

The core of my thesis is simple. Nvidia sells the picks and shovels for what Jensen Huang calls “the largest infrastructure expansion in human history”, and the buyers are the richest companies on earth.

OpenAI committed to at least 10 gigawatts of NVIDIA systems. Meta signed up for millions of Blackwell and Rubin GPUs. CoreWeave is building 5+ gigawatts of AI factories by 2030. When that customer list keeps growing, I keep adding.

Reason 1: A financial engine at a scale I have not seen before In the quarter reported May 20, 2026, NVIDIA put up revenue of $81.6 billion, growing 85.23% year over year. Non-GAAP gross margin landed at 75%. Free cash flow for the quarter hit $48.55 billion, on top of FY2026 free cash flow of $96.58 billion.

The company has now beaten EPS estimates for 12 consecutive quarters, with the most recent report of $1.87 topping the $1.77 consensus. A trailing P/E of 30 with a PEG of 0.59 and a forward P/E of 22 tells me the market is still pricing this like a normal chip company.

Reason 2: A widening moat Data Center revenue was $75.25 billion, up 92% year over year, with networking alone growing 199%. The company guided Q2 to $91 billion. Behind that guide sits $119 billion in total supply-related commitments. CUDA, NVLink, InfiniBand, Spectrum-X, and the upcoming Vera Rubin platform mean customers are buying a full stack they cannot easily swap out.

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Reason 3: Capital returns have shifted gear On May 18, 2026, the board raised the quarterly dividend from $0.01 to $0.25 per share and authorized an additional $80 billion in buybacks on top of $38.5 billion remaining. NVIDIA returned $20 billion to shareholders in a single quarter and $41.1 billion across FY2026. For a long-term holder, that is compounding I can feel.

The risk I take seriously China is the real one. NVIDIA shipped zero H20 Data Center compute units to China in Q1, against $4.6 billion in the year-ago quarter, and Q2 guidance assumes none. Hyperscalers also account for roughly 50% of Data Center revenue, which is real concentration.

My thesis holds because the $91 billion Q2 guide and 85.23% growth were produced with China explicitly stripped out. Demand outside that one geography is already setting records.

Why the buy button stays active The stock trades at $194.97, down 7.55% over the past month, while the underlying business produced net income of $58.32 billion in one quarter.

Sovereign AI builds across the UK, Germany, France, South Korea, and India, the Vera Rubin ramp, and DRIVE Hyperion in autos give me a multi-year roadmap with cash to fund every step. I keep buying because the cash flow keeps showing up, and the moat keeps getting deeper.

Don't wait: the analyst who called NVIDIA in 2010 just revealed his top 10 AI stocks. See the full list FREE now.

Contact [email protected] for any questions or corrections.

Nvidia stock lags far behind the 94% gain for the PHLX Semiconductor Index for 2026 so far.

Nvidia CEO Jensen Huang Jung Yeon-je / AFP via Getty Images Unlike many of its Big Tech peers, there's no free lunch at Nvidia.

A recent X thread by software engineer and industry analyst Gergely Orosz, who claimed that snacks and coffee aren't free at the chip giant, drew attention to the chip giant's relatively sparse workplace perks.

Two former employees told Business Insider that cafeteria meals aren't free but are subsidized, so some of the food's cost is covered by Nvidia. Some beverages, such as coffee, are complimentary, but select bottled beverages and drinks purchased from on-site cafés were not.

The policy reflects a different philosophy from the Silicon Valley perk wars that once defined Big Tech. While rivals used free meals, gyms, and lavish campuses to keep employees in the office, former employees described a culture rooted in frugality, where lavish workplace perks took a back seat to the work itself.

Big Tech is now increasingly clamping down on perks in a new era of efficiency. Amazon and Apple also don't offer free food. Nvidia's practice stands in contrast to Google, which continues to offer chef-prepared meals and microkitchens stocked with snacks. Meta is reportedly trying to improve its microkitchens amid morale challenges at the company.

As tech companies rethink workplace perks in an era of AI and cost discipline, Nvidia's understated approach has become less of an outlier.

The former employees attributed the approach to different facets of Nvidia's culture.

"Philosophically, I think Jensen has a general belief about separation of pleasure and work," one said, noting the company didn't have "ping-pong tables, a company gym, massages-on-request, or stuff like that."

The second added that Huang — a noted foodie — wants employees to be able to do their "life's work," which requires a healthy balance. "Other workplaces where everything is free are implicitly trying to coax employees into staying in the office as much as possible — Nvidia has the exact opposite philosophy."

"Being frugal is deeply rooted in Nvidia's DNA," said a third employee who no longer works at the company. "Traditionally, hardware companies have always been operating at very thin margins, far below what software companies were doing."

To this end, Nvidia vice presidents fly economy and don't have executive assistants — a practice that's been attributed to its "one team" culture of equality.

The food policy doesn't appear to bother Nvidia employees.

"There was so much exciting work going on that these types of things were really not an issue," a fourth former employee said. "Food would be your last concern as long as you could get it ASAP and return to your desk."

Nvidia did not respond to a request for comment from Business Insider.

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Geoff Weiss You're currently following this author! Want to unfollow? Unsubscribe via the link in your email.

Geoff Weiss is a senior reporter on Business Insider’s tech team, where he writes about AI startups and Y Combinator, the intersection of AI and the media industry, and workplace dynamics within top AI labs and chip companies.Previously, Geoff was on the media desk, covering YouTube and Netflix, and themes like the intersection of Hollywood and the creator economy. His work on Netflix’s video podcasting ambitions and Mr Beast’s lessons for Hollywood won second and first prize, respectively, at the 2025 LA Press Club Awards.Prior to joining Business Insider, Geoff was the senior editor of Tubefilter and a staff writer at Entrepreneur. He graduated from New York University with a degree in English Literature.He can be reached at [email protected], on Signal @geoffweiss.25, and on LinkedIn. Have a tip? Use a personal email address and a nonwork device; here's our guide to sharing information securely.Selected stories:Nvidia crushed its quarter — and CEO Jensen Huang said in a leaked all-hands that 'the market did not appreciate it'Nvidia will foot the bill for Trump's new visa fees. Here's what CEO Jensen Huang told staff.Massive AI salaries and RTO are fueling a real estate boom in San Francisco: 'It's going to rain money'The AI talent wars are ricocheting across startups. Here's how they're competing with Big Tech.

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Over the last five years, Nvidia (NVDA +1.30%) has been the quintessential millionaire-maker stock -- returning roughly 950% compared to the S&P 500's relatively modest gain of 74%. The company's powerful graphics processing units (GPUs) are the workhorses of the generative artificial intelligence (AI) industry. And its advantages in scale and technology have helped it stay ahead of the competition.

That said, Nvidia's stock price growth is beginning to stall as investors balk at its huge size and pivot to other sides of the AI infrastructure opportunity. Let's dig deeper to see if the company has what it takes to break out of its slump and continue generating market-beating returns.

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Business is still booming The generative AI megatrend shows no signs of slowing anytime soon. In fact, it may be heating up. Analysts at Evercore and Bank of America expect big tech's AI-related capital spending to exceed $1 trillion in 2027 -- up from around $800 billion to $900 billion this year. Most of this money is going to advanced hardware needed to run massive data centers.

Nvidia's chips remain highly relevant, which is reflected in the company's first-quarter earnings results. Revenue jumped 85% year over year to $81.6 billion, which is an incredible number for a business that is already so large. And as in previous quarters, overall growth was driven by growth in the company's data center segment, which recently announced exciting new offerings such as the Vera Rubin Platform, designed to facilitate the rise of agentic AI by removing processing bottlenecks.

Many industry watchers believe agentic AI represents the next phase of the technology. Unlike earlier AI systems, it is designed to independently plan and make decisions with limited human oversight, making it ideal for helping automate a variety of industries. And if the technology takes off as expected, it could help Nvidia maintain its elevated growth rate.

Management is returning value to shareholders Nvidia's success isn't limited to its top line. The company's technological edge gives it strong pricing power and operating leverage. Net income soared 211% year over year to $58.3 billion, and management is getting increasingly serious about returning much of it directly to shareholders.

As of May, Nvidia has increased its cash dividend from just $0.01 per share to $0.25 per share (a yield of around 0.5%). More importantly, management authorized an additional $80 billion in stock repurchases on top of the $38.5 billion remaining from its previous program.

Image source: Getty Images.

Investors tend to love buybacks because they reduce the number of a company's shares outstanding, giving every investor a higher claim on the company's future earnings and cash flow. They tend to encourage stock price growth and, unlike dividends, they aren't taxed as regular income, which can make a tremendous difference over the long term.

Nvidia's huge push toward buybacks marks a sharp divergence from other technology giants like Amazon, Microsoft, and Micron Technology, which are instead plowing cash back into AI-related capital expenditures like data centers or expanded production capacity. Nvidia's strategy is arguably less risky because it relies on internally generated cash instead of debt or dilution like some of the alternatives in the tech industry.

With a market cap of $4.72 trillion, Nvidia isn't a millionaire-maker stock anymore because, even in the best-case scenario, rapid multibagger growth seems unrealistic from such a high level. The company's sky-high margins will also eventually come down as customers substitute in-house solutions for Nvidia products and rivals catch up technologically.

That said, with a forward price-to-earnings (P/E) multiple of just 22.7, most of these challenges are already priced into Nvidia's valuation. And management's aggressive buyback policy will benefit shareholders over the long haul. Investors should view Nvidia stock as a value-oriented pick in the AI industry instead of a big growth opportunity.

If you asked me which stock would have a better 2026, Nvidia (NVDA +0.93%) or Advanced Micro Devices (AMD +2.74%), I would have said Nvidia without hesitation. If the only thing you had to look at were business results, you'd likely come to the same conclusion as my projection.

However, the market is in love with AMD's stock, and it has trounced Nvidia's year-to-date performance. Since the start of 2026, AMD's stock has risen a jaw-dropping 144%. Nvidia has barely done anything, rising about 4%. Clearly, the market prefers AMD to Nvidia stock.

But will that continue into the latter half of 2026? Let's take a look.

Image source: Getty Images.

AMD is putting up a fight in the AI computing arena AMD and Nvidia are both deeply involved in the AI computing build-out. Nvidia is more exposed than AMD, but AMD still gets over half its revenue from data center-related products. From the start of the AI race, Nvidia's products were hands down better than AMD's. Additionally, Nvidia had its graphics processing unit (GPU) controlling software, CUDA, that was ages ahead of AMD's offering. This allowed Nvidia to capture a large market share, and it became the go-to computing unit for all AI workloads.

AMD has clawed itself back into the mix and launched several exciting products, like its Instinct MI350 series. This landed AMD several deals, including one with OpenAI. All of this added to the hype around AMD's stock indicating that it could become a legit competitor in the AI data center landscape.

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This caused the stock to surge throughout 2026, as the prevailing sentiment is that AMD has caught up with Nvidia. The problem is that that's just not the case.

Nvidia is crushing AMD in nearly every financial metric The "AMD is back" argument falls apart when you compare its results to Nvidia's. In the first quarter, AMD's data center division grew at a respectable 57% year-over-year pace and a 7% quarter-over-quarter pace. Nvidia nearly doubled those results, with data center revenue rising 92% year over year and 21% quarter over quarter. As for size, Nvidia is nearly 15 times larger, with its data center division generating $75.2 billion in Q1, and AMD's totaling $5.8 billion. In the company-wide view, Nvidia is still winning the race.

NVDA Net Income (TTM) data by YCharts.

So, how is Nvidia's stock underperforming AMD's so badly? In my view, the market has become irrational with AMD's stock. After its major run-up, AMD now trades for a shocking 71 times forward earnings. Nvidia trades at a far cheaper and more reasonable 21.6 times forward earnings. That means AMD's earnings must more than triple after 2026's growth is accounted for, just to trade at the same level that Nvidia does today.

That seems like an absurd mismatch of valuation and expectations, and with Nvidia not shrinking at all, it makes AMD seem like a worse stock pick for the future. I'm not betting against AMD stock in any way, as the market can remain irrational longer than I can stay solvent. Still, after looking at AMD and Nvidia, I have a hard time rationalizing investing in AMD versus Nvidia.

AMD appears to have already taken some of Nvidia's market share, according to the stock's sentiment (it really hasn't), while Nvidia appears to be losing every battle it's getting into (it's not). There is a huge mismatch in expectations, and I think investors would be smart to take advantage of it by selling AMD shares and instead investing that into Nvidia's stock, as it looks like a great value right now.

Just because Nvidia is the biggest company in the world, it doesn't mean it has reached a ceiling. It can go far higher, and if expectations come back to reality for other AI competitors, Nvidia's stock is primed to skyrocket.

It has been a frustrating year for Nvidia (NVDA +0.39%) investors, as the tech giant's shares have barely delivered any gains so far in 2026. The PHLX Semiconductor Sector index, for comparison, has registered remarkable gains of 79% this year.

However, it is difficult to justify Nvidia's underperformance in the first half of 2026. The company is on track to deliver better results this fiscal year, driven by the artificial intelligence (AI)-fueled demand for its chips. So, will the market give Nvidia enough credit for its impressive financial performance and help the stock rally in the second half of 2026?

Let's find out.

Image source: The Motley Fool.

Nvidia's Vera Rubin chips could be a catalyst for the stock Nvidia is all set to begin shipments of its next-generation Vera Rubin processors this fall. The company recently noted that Vera Rubin chip systems are now in full production, and demand for these chips appears to be quite healthy. I say this because Nvidia noted earlier this year that it has a $1 trillion order pipeline for the Blackwell and Vera Rubin chip architectures for 2026 and 2027.

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That's a significant upgrade over the $500 billion worth of orders it was anticipating for 2025 and 2026. A nice chunk of those orders is likely to be for the Rubin processors. That's because Nvidia claims that Vera Rubin will deliver 10 times higher performance per watt over Blackwell systems, as reported by CNBC. So, it is easy to see why companies such as Meta Platforms, Anthropic, OpenAI, Amazon, Microsoft, and Google are poised to deploy these chips to run AI workloads in data centers.

What's more, Nvidia is expected to increase the price of Vera Rubin systems by 25%, according to market research and analysis firm The Futurum Group. So, Nvidia's margin profile could improve, leading to a stronger jump in earnings this year. What's worth noting is that Nvidia's earnings are predicted to increase by 88% in fiscal 2027 (which ends in January 2027) to $8.96 per share.

That would be a significant step-up from the 60% earnings growth Nvidia delivered in fiscal 2026. IDC forecasts that the semiconductor industry's revenue could jump by 53% in 2026 to $1.29 trillion. Nvidia, meanwhile, could witness an 82% jump in revenue this fiscal year to $392 billion. So, there is a likelihood that Nvidia's earnings will grow faster than the overall semiconductor market this year. After all, its top-line growth is poised to outpace the industry, and a potential increase in the price of its Vera Rubin systems could lead to a larger increase in earnings than analysts project.

This is precisely why buying Nvidia could prove a smart move after its poor performance in the first half of 2026.

The stock is too cheap to ignore right now With a price-to-earnings ratio of 29, Nvidia stock is an absolute bargain right now. The iShares Semiconductor ETF, which tracks and invests in semiconductor companies, trades at a much more expensive 75 times earnings. This cheap valuation could pave the way for a strong bull run in Nvidia in the second half of the year.

Assuming it trades at even 40 times earnings by the end of the fiscal year and clocks $8.96 in earnings per share, Nvidia's stock price could jump to $358. That's a potential upside of 85%, which is why it would be a good idea to buy this AI stock before it starts rallying in the second half of 2026.

Harsh Chauhan has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Amazon, Meta Platforms, Microsoft, Nvidia, and iShares Trust-iShares Semiconductor ETF. The Motley Fool has a disclosure policy.

NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) stock has cooled off this summer, but the 24/7 Wall St. price target says the pullback looks like a setup for further upside. Shares closed at $192.53 on June 26, 2026, down 8.62% on the week, even as Wall Street remains overwhelmingly bullish. Nvidia is the most-owned megacap in the AI build, and our model thinks the recent dip widens the runway for further upside.

Our 24/7 Wall St. price target for NVIDIA is $245.91 over the next 12 months, implying 27.73% upside. The recommendation is buy, with a confidence score of 90%, which we consider high.

24/7 Wall St. Price Target Summary Metric Value Current Price $192.53 24/7 Wall St. Price Target $245.91 Upside 27.73% Recommendation BUY Confidence Level 90% A Summer Wobble Inside a Bigger Uptrend NVIDIA is up 24.36% over the past year and 3.36% year to date, but the last month has been ugly, with shares off 9.34%. The stock sits 27% below its 52-week high of $236.26 and well above the $151.29 low.

Fundamentals have not cracked. Q1 FY2027 revenue hit $81.615 billion, up 85.23% year over year, with non-GAAP EPS of $1.87 beating expectations. Data Center revenue reached $75.246 billion, up 92%, with networking revenue tripling at 199% growth. Q2 guidance came in at $91 billion. NVIDIA also launched the BioNeMo Agent Toolkit for life sciences, extending the platform beyond pure compute.

Why Bulls See a Breakout Toward $300 The bull case rests on Blackwell. CEO Jensen Huang called the AI factory buildout “the largest infrastructure expansion in human history”, and NVIDIA has locked in $119 billion in supply commitments. Multigenerational deals with OpenAI (10GW), Anthropic (1GW), Meta, Microsoft, Google Cloud, and Oracle anchor demand into the Vera Rubin platform.

Of 61 covering analysts, 58 rate NVDA Buy or Strong Buy versus just 1 Sell. The Street consensus target is $298.93. If Blackwell 300 ramps at 75% gross margins and Q2 results come in near guidance, the bull scenario points to $259.20, a 34.63% one-year return.

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The Risks Worth Watching The bear case starts with concentration. The model assumes zero China Data Center compute revenue, and further export tightening hits sentiment more than numbers. Supply-chain reliance on TSMC, a planned cash tax jump in Q2, and gross margin risk during architecture transitions are real. Retail conviction is wobbling, with Reddit traffic this month flagging AI stock losses and Chinese model parity on Huawei silicon.

Insider selling has picked up, with 9 recent transactions net selling. Bulls counter that these are routine 10b5-1 trims against $20 billion in Q1 buybacks and a fresh $80 billion repurchase authorization. The bear scenario still produces $212.99, a 10.62% gain.

NVIDIA Price Prediction 2026-2030 At $192.53, the 24/7 Wall St. price target of $245.91 leans on real earnings power rather than relying on multiple expansion, and even the bear case is positive. Key signals to monitor: whether Q2 prints above the $91 billion guide, whether gross margins hold above 73%, and whether export rules expand beyond H20. The current pullback is worth watching closely.

Looking further out, here is where the 24/7 Wall St. price target model projects NVDA could trade, assuming current growth trajectories hold and the AI capex cycle extends through the Vera Rubin generation.

Year 24/7 Wall St. Price Target 2026 $245.91 2027 $285.00 2028 $320.00 2029 $355.00 2030 $391.74 These projections assume NVIDIA holds platform leadership through Vera Rubin and hyperscaler capex grows in line with current commitments. A China policy reversal would be meaningful upside, while a credible domestic Chinese alternative or hyperscaler in-house silicon shift would compress the trajectory.

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SHANGHAI, CHINA - JUNE 24: Nvidia logo is seen during the 2026 Mobile World Congress (MWC) Shanghai on June 24, 2026 in Shanghai, China. Mobile World Congress (MWC) Shanghai, slated for June 24 to 26 this year, is Asia's largest and most influential connectivity ecosystem event, with global leaders and innovators set share their visions for the future of connectivity at this showpiece in east China. (Photo by Long Wei/VCG via Getty Images)

VCG via Getty Images

This article was written by Doug Nathman, with research by his team at Trefis.

Currently priced near $195, NVIDIA (NVDA) is positioned for an approximate 51% upside in the upcoming three years under a conservative assumption. Such a significant shift warrants a closer examination of its origins. Revenue compounding drives the growth, although the multiple plays a notable role along the journey. Below is the operational basis for the calculations:

While the industry focuses on its GPUs, the company is making strides into a completely new sector. Management has introduced Vera, its inaugural CPU specifically designed for agentic AI. This initiative targets a market that NVIDIA has not tapped into before.

This strategic shift underscores why the growth projection hinges on revenue. The current Data Center operation serves as a massive, compounding driver, while the introduction of the Vera CPU line adds a separate, distinctive growth channel.

NVDA Key Metrics

Trefis

How The Calculations Are MadeThree forecasts contribute to the upside figure. Revenue is expected to compound at 30.0% each year over three years, marking a decline from the LTM 70.7% rate, which aligns with the deceleration evidenced in the historical data. Net margin relaxes from 63.0% to 57.6% as the current LTM reverts to the long-term average. Additionally, the multiple has adjustments to undergo that are unfavorable for the company. NVDA’s P/E currently stands at 29.8x, which is less than its 3-year average of 56.0 times. The scenario further reduces it to 22.3 times due to a slower expected growth rate that fails to sustain even the current multiple.

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When these three components are combined, earnings rise from $159.6 billion to approximately $320.5 billion, a 101% increase. Applying the diminished multiple to this figure results in a stock price near $294.80, which is just 51% higher than the present value. The multiple impacts earnings prior to the adjustments reflecting on the share price.

Is NVDA Capable Of Achieving This?The Vera CPU serves as the essential catalyst yet to be accounted for in the current run rate. Management asserts that Vera unveils an entirely new $200 billion market for the company. More specifically, they already anticipate nearly $20 billion in total CPU revenue within this year.

What Could Potentially Undermine It?The main risk lies in the possibility that this new CPU introduction may not progress as swiftly as previous launches. When asked to compare the Vera Rubin launch to past successes, management acknowledged the difficulty in making such an evaluation at this time. They admitted it is somewhat premature to determine how quickly the new architecture will scale.

Considering An Investment In NVDA At Current PricingInvestors are investing in consistent compounding, rather than a revaluation or margin enhancement. The assumption is that revenue continues to grow at an approximately projected rate; if it falls short, the calculations lack alternative directions.

The $20 billion in anticipated Vera revenue is too significant to overlook, rendering the uncertainty around the ramp an understandable concern.

Is It Wise To Invest In NVIDIA?A thorough three-year analysis on an individual stock remains a concentrated investment, as historical volatility during previous market turmoil indicates. Investors who conduct analyses like this for individual holdings often seek a similar methodology across a diversified portfolio, partly for discipline, and partly because even the most straightforward single-stock thesis can unravel due to factors not accounted for in the numbers.

The Trefis High Quality (HQ) Portfolio blends analytical precision with a proactive outlook across 30 stocks, featuring a consistent selection framework along with a sizing and re-balancing strategy designed to achieve growth without the risks associated with the individual stock analysis just discussed.

By selecting 30 stocks with high conviction, the HQ approach has historically outperformed a benchmark composed of the three major indices – the S&P 500, S&P Mid-cap, and Russell 2000.

Former House Speaker Kevin McCarthy, now chairman of the Alpha Institute, told CNBC on June 29, 2026 that artificial intelligence is on track to become the rare issue both parties run against in the next presidential cycle. That is a strange thing to predict about a technology currently powering the most expensive capital-expenditure boom in American corporate history. But McCarthy thinks the politics have already turned, and that investors with exposure to data centers, chip designers, and the utilities feeding them should pay attention before policy catches up to the mood.

Why McCarthy thinks 2028 becomes an anti-AI election McCarthy told CNBC, “I’ve never seen one issue flip so hard, and I don’t think you’re going to see one party in one way and another party in another. You could have in the year 2028, both nominees running against AI.” The usual pattern in American politics is that technology splits the parties. Crypto, social media moderation, and electric vehicles all produced a pro side and an anti side. AI, in his telling, is collapsing into a single bipartisan villain.

The macro backdrop is not helping the technology’s case. University of Michigan consumer sentiment sat at 44.8 in May 2026, down from 61.8 in July 2025, which is well into what the index treats as recessionary territory. When voters feel that pessimistic, they look for something to blame, and a technology going after white-collar work makes a convenient target.

The myth-versus-data argument on water, energy, and jobs McCarthy’s frustration is that the populist case against AI rests on claims he says the underlying data does not support. “AI has kind of become the boogeyman already, because if you think about it, there’s this myth. People think these data centers, you’re going to take your water, take your energy. When some of this data will show that it lowers your energy price,” he told CNBC.

The picture from government and academic reports is more complicated than either side admits. The Department of Energy projects data centers will account for up to 12% of U.S. electrical demand by 2028, and Colorado utility Xcel Energy has proposed an electric resource plan that could add over 6,000 megawatts of new generation, partly to serve data centers.

McCarthy’s labor point holds up better in the current data. JOLTS job openings hit 7.62 million in April 2026, the high of the past year, with unemployment steady at 4.3%. Electricians and HVAC trades feeding hyperscale construction are part of that demand.

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The policy-lag risk for AI-exposed portfolios “I have a fear that the policy has not kept up… we’re living through an industrial revolution that is much faster and policy is not keeping up with it, and there’s going to be discomfort,” McCarthy told CNBC. His Alpha Institute, he said, is trying to “get the policy right before” populism forces reactive rules.

That regulatory vacuum is what should focus investor minds. Executive Order 14179, Removing Barriers to American Leadership in Artificial Intelligence, currently tilts federal policy toward buildout. State legislatures are moving the other way on water permits, large-load tariffs, and residential rate protection, and that patchwork is where the real friction shows up for hyperscalers and the utilities supplying them.

Why investors should care The trade most exposed to a McCarthy-style backlash runs wider than any single chip designer. It spans data-center developers, grid-interconnection queues, and AI-infrastructure suppliers whose growth assumptions quietly require permissive permitting through 2030.

NVIDIA (NASDAQ:NVDA | NVDA Price Prediction) sits at the top of that stack with capital flooding the buildout.

McCarthy is making a probabilistic claim about 2028. The investing question is whether the political risk on AI infrastructure is currently priced into the names benefiting from it. His answer, fairly clearly, is no.

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June 29, 2026 09:00 ET  | Source: Bit Origin Ltd

-16 NVIDIA Blackwell B300 AI servers expected to commence operations following expected Q3 2026 delivery, expected to generate approximately US$360,000 in monthly revenue before operating expenses-

-Marks the first milestone in the Company’s previously announced expansion into AI computing and data center services-

SINGAPORE, June 29, 2026 (GLOBE NEWSWIRE) -- Bit Origin Ltd (NASDAQ: BTOG) ("Bit Origin" or the "Company"), an emerging growth company focused on AI computing infrastructure, digital asset innovation and blockchain-based strategies, today announced the acquisition of approximately US$11 million of NVIDIA Blackwell B300 AI infrastructure assets.

The acquired assets consist of sixteen (16) NVIDIA Blackwell B300 AI servers that have already been purchased by the seller and are currently expected to be delivered during the third quarter of 2026. Upon delivery, the servers are expected to be deployed at a data center facility in Malaysia pursuant to previously executed hosting arrangements. The Company has also acquired the benefit of previously executed customer deployment arrangements relating to the infrastructure. Based on these customer agreements, the Company expects the B300 servers, following their expected delivery and deployment, to generate approximately US$360,000 in recurring monthly revenue before operating expenses.

The aggregate purchase price consists of US$1 million in cash and US$10 million in equity, in the form of pre-funded warrants issued by the Company.

The acquisition represents the Company's first transaction involving next-generation NVIDIA Blackwell AI infrastructure and marks another important milestone in the execution of Bit Origin's AI infrastructure strategy announced earlier this year.

Strategic Expansion into AI Infrastructure

In April 2026, Bit Origin announced its strategic expansion beyond digital asset mining into AI computing infrastructure, GPU computing services and related digital infrastructure opportunities.

Unlike development-stage AI infrastructure projects, the acquired assets are supported by previously executed supplier arrangements, customer agreements and data center hosting arrangements. Following the expected delivery during the third quarter of 2026, the Company expects the infrastructure to commence commercial operations in Malaysia and begin generating recurring infrastructure-related revenue.

Management believes demand for high-performance GPU infrastructure continues to be driven by the rapid adoption of artificial intelligence technologies, large language models, enterprise AI applications and next-generation computing workloads. As enterprises increasingly deploy AI-powered products and services, access to reliable, scalable computing infrastructure has become an increasingly critical component of the global digital economy.

The Company believes this acquisition strengthens its position within the evolving AI computing ecosystem while establishing a foundation for continued expansion into high-performance computing infrastructure.

Management Commentary

"This acquisition represents another important milestone in the execution of our AI infrastructure strategy," said Mr. Jinghai Jiang, Chairman and Chief Executive Officer of Bit Origin.

"We are pleased to acquire next-generation NVIDIA Blackwell B300 AI infrastructure together with contracted customer deployment and hosting arrangements. We expect the servers to be delivered during the third quarter of 2026 and, upon deployment in Malaysia, to generate approximately US$360,000 in recurring monthly revenue before operating expenses, providing an initial foundation for our AI infrastructure business."

Mr. Jiang continued, "As demand for AI computing resources continues to accelerate globally, we believe high-performance GPU infrastructure represents an attractive long-term opportunity. This transaction expands our exposure to AI infrastructure through revenue-generating assets while establishing a scalable platform for future growth. We intend to continue evaluating additional opportunities involving AI infrastructure, GPU computing services, data center operations and other high-performance computing assets as part of our broader growth strategy."

About Bit Origin Ltd

Bit Origin Ltd (NASDAQ: BTOG) is an emerging growth company focused on digital asset innovation and blockchain-based strategies, including the development of AI computing infrastructure, digital infrastructure opportunities and digital asset treasury initiatives.

For more information, please visit www.bitorigin.io.

Safe Harbor Statement

This press release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995. Forward-looking statements include statements regarding the anticipated closing of the transaction, expected revenue generation, future AI infrastructure opportunities, expansion into AI computing services, and the Company’s long-term strategic initiatives. These forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from those expressed or implied herein. The Company undertakes no obligation to update any forward-looking statements except as required by law.

Company Contact:

Bit Origin Ltd

Mr. Jinghai Jiang
Chairman and Chief Executive Officer

Email: [email protected]

In a June 29 X post, Ali Martinez revealed that, after confirming a bearish breakout, Nvidia (NASDAQ: NVDA) stock price target stands at $170.

Specifically, the prominent on-chain analyst revealed that NVDA shares have cleared the ‘neckline’ of a head-and-shoulders pattern, indicating their descent is likely to continue.

Head-and-shoulders is a technical analysis (TA) pattern that occurs during a trend reversal either from bullish to bearish or from bearish to bullish. In the case of Nvidia stock in 2026, the left shoulder began forming during the April rally that ended with a drop in early May and went on to form a head later in the same month.

The right and lower shoulder finally took shape in mid-June with a new climb above $210 before the most recent trading broke the ‘neckline,’ indicating a deeper correction is imminent.

2026 Nvidia stock price performance Notably, the June 29 extended session also featured a slight recovery as NVDA shares rallied 0.90% from their latest – Friday – close to $194.26.

Under the circumstances, the confirmation of the sell signal might only come after the Monday morning bell as volume increases, diminishing the impact of any individual trades.

Should Martinez’s forecast prove correct, it would indicate that, after dropping 14.19% in June, Nvidia stock is set to plunge another 11.70% to $170.

Such a move could also prove significant for the wider market as NVDA shares have served as something of a leader among big tech firms due to their exceptional rally during the artificial intelligence (AI) boom that started with the initial public release of ChatGPT.

So far, despite the technological narrative remaining dominant with most analysts seeing further potential in the greater sector with a particular focus on memory and central processing units (CPUs), investors have apparently turned more cautious.

Indeed, in stark contrast to its performance in recent years, Nvidia stock is underperforming the benchmark indices – for example, NVDA shares are 1.95% up to their latest close at $192.53 year-to-date (YTD), and the S&P 500 is up 7.23% in the same timeframe – with June providing a period of particular volatility amidst a growing debate over AI return on investment (ROI).

Featured image via Shutterstock

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June 29, 2026 07:00 ET  | Source: NN, Inc.

CHARLOTTE, N.C., June 29, 2026 (GLOBE NEWSWIRE) -- NN, Inc. (“NN” or the “Company”) (NASDAQ: NNBR), a global diversified industrial company that engineers and manufactures high-precision components and assemblies with six sigma quality, today provided an update on its rapidly growing Data Center business. NN’s combined Data Center and Electric Grid business is already its 2nd largest business, with a further goal to grow the business into the Company’s largest business by sales. The Data Center & Electric Grid end markets are top targeted growth markets for the Company along with Medical products and Defense and Electronics products.

NN has secured a significant amount of additional 2026 immediate-supply awards for liquid cooling products that go into NVIDIA AI data center racks. The new awards in this announcement are additive to prior communicated awards and greatly increase the size of NN’s liquid cooling product portfolio for AI data center racks.

NN is on its way to having 52 dedicated machines to make liquid cooled products for its data center business. 50 machines will be dedicated production lines and an additional 2 machines will be dedicated to making samples for new business. NN has already pre-sold 100% of the production capacity. NN is continuing to prospect globally and is using its global business development team and global machining footprint to prospect for additional business in this fast-growing area. In 2026, NN has attended Data Center tradeshows in the United States, Europe, and China.

Harold Bevis, President and Chief Executive Officer of NN, Inc. commented, "The liquid-cooled AI data center market is one of our targeted end markets for growth. We announced the successful launch of a new product line in Q1 2026. It is a custom-designed, stainless-steel product line for the liquid-cooled data center market. Since then, we have secured multiple AI data center awards, have invested in an initial complement of 17 next-generation, high-speed, high-precision CNC machines at our Wuxi, China plant, and began production. We have a big set of data center products already but we are just beginning. We make products that go into both the electrical system and cooling system for Data Centers and produce these products in multiple plant locations.

Today, we are pleased to announce that we have tripled the size of the liquid cooling product line that just launched in Q1 2026. Specifically, we have secured another set of multi-year, multi-product awards for stainless-steel cooling products for the NVIDIA supply chain. NN is now underway with procuring an additional 30 new machine centers on top of the 17 new CNC machine centers we previously announced. Additionally, we have successfully repurposed and retooled 5 automotive CNC production centers to become dedicated data center production. We have a strategic goal to rotate out of commodity auto products and this accelerates the achievement of that objective.”

Bevis continued, “We are building a meaningful position in the global supply chain for liquid cooled AI systems. The Wuxi plant had approximately 200 CNC machine centers before successfully entering the data center business. These additional 47 machine centers bring the total in that plant to approximately 250 CNC machine centers when this expansion is complete. We have large aspirations with our global footprint, and the industry needs NN to scale up and supply more. The AI data center liquid cooling industry is scaling very rapidly, and we are participating in the global data center buildout. This is a natural product fit as we are experienced veterans in pressurized fluid management, stainless steel part production, exceptional repetitive quality levels at high volumes, electropolishing, abrasive flow machining, debris-free and leak-free products, and fast innovation.

We have a dedicated company effort to grow Data Center products, and we are happy to have secured our next set of new awards. This expansion and ramp up is underway now during Q2 2026 and will be additive to our 2026 sales. Based on equipment lead times, the 47th new machine will be installed in November 2026. We are underway prospecting for additional awards and developing new products. As mentioned, the 47 new machines in this announcement will go into NN’s Wuxi, China plant and it will be supplying parts into NVIDIA’s Asia supply chain in China, Taiwan, and Vietnam. NN’s Wuxi China plant is a global low-cost plant that is well known in the metal part making industry. It is in an ideal location for supplying the metal parts that go into the global supply chain for AI data center racks. We believe these data center racks which are being produced in Asia are coming back to the US and being installed in data centers being built in the United States AI market.”

Bevis concluded, “As next generation supply chain decisions are being made in the data center industry, NN intends to use its global footprint of machining plants to participate further. This is a multi-billion market that is scaling up right now, and these computing racks are the hardware behind the expanding use of AI and cloud computing. These new awards fit within NN’s previously issued new wins guidance for achieving $80 to $90 million of accretive new business during 2026. We will combine this new information along with other information and adjust 2026 and 2027 sales and EBITDA guidance, if needed, during NN’s next business and guidance update when we release Q2 earnings in early August. We look forward to discussing this big advancement during that time.”

About NN’s Fluid Management Products

NN is a leader in precision fluid management products for over 40 years. The Company makes precision metal fluid management components including valve body, socket body, valve seat, sealing seat, needle, plunger, plug base, socket base, guides, and threaded connector parts. Given its long-term expertise, NN can make these products in a variety of manners across high-mix, medium-speed single spindle machines as well as high-volume, high-speed production with multi-spindle machines and rotary transfer systems. It makes these products in-house in its plants in China, Europe, South America, and North America. NN makes these products today and has for decades under multi-year contracts for many of the top OEMs in the world. The goal is leak-free, debris-free products that never fail during the life of the equipment.

NN's existing liquid management products precisely fit the requirements of data center applications, and the demanding performance and quality requirements of AI data center and cloud customers are a direct use of the Company’s existing capabilities. Furthermore, next generation computing designs require even higher power use and even higher heat generation, which will lead to next-generation liquid-cooled computing systems and components. The Company can already make products that are advanced beyond today’s requirements. NN has delivered six sigma quality, micron-level tolerance parts for combustion engines for decades. The Company’s decades of global experience and footprint are directly applicable to this new area.

About NN

NN, Inc., a global diversified industrial company, combines advanced engineering and production capabilities with in-depth materials science expertise to design and manufacture high-precision components and assemblies for a variety of markets on a global basis. Headquartered in Charlotte, North Carolina, NN has facilities in North America, Europe, South America, and China. For more information about the Company and its products, please visit www.nninc.com.

Forward-Looking Statements

This press release contains express and implied forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995, including, but not limited to, statements regarding future growth of NN’s liquid-cooled AI data center business, the procurement and timing of additional machines to support the liquid-cooled AI data center business, NN’s aspirations , the size and future outlook of the data center market, NN’s competitive position in the data center market, , expected new business wins for 2026, the Company’s 2026 performance and other statements that are not historical facts.

Forward-looking statements generally will be accompanied by words such as “anticipate,” “believe,” “could,” “estimate,” “expect,” “forecast,” “guidance,” “intend,” “may,” “will,” “possible,” “potential,” “predict,” “project”, “achieve,” “growth,” “enable,” “improve,” or the negative of these terms, and similar words, phrases or expressions that convey uncertainty of future events or outcomes. Forward-looking statements involve a number of risks and uncertainties that are outside of management’s control and that may cause actual results to be materially different from such statements. Such factors include, among others, general economic conditions and economic conditions in the industrial sector; competitive influences; risks that current customers will commence or increase captive production; risks of capacity underutilization; quality issues; inflationary pressures and material changes in the cost or availability of raw materials, supply chain shortages and disruptions, the availability of labor and labor distributions along the supply chain; our dependence on certain major customers, some of whom are not parties to long-term agreements (and/or are terminable on short notice); the impact of acquisitions and divestitures, as well as expansion of end markets and product officers; our ability to hire or retain key personnel; the restrictions contained in our debt agreements; the level of our indebtedness and our ability to obtain financing at favorable rates, if at all, or to refinance existing debt as it matures; our ability to secure, maintain or enforce patents or other appropriate protections for our intellectual property; the impact on climate change on our operations; economic, social and geopolitical instability, military conflict, current fluctuation, and other risks of doing business outside of the United States; and uncertainty of government policies and actions in respect to global trade and tariffs, including the potential impacts of tariffs on the United States economy, the economy of other countries in which we conduct operations and our industry, cyber liability or potential liability for breaches of our or our service providers’ information technology systems or business operations disruptions. The foregoing factors should not be construed as exhaustive and should be read in conjunction with the sections entitled “Risk Factors” and “Management’s Discussion and Analysis of Financial Condition and Results of Operations” included in the Company’s filings made with the U.S. Securities and Exchange Commission. Any forward-looking statement speaks only as of the date of this press release, and the Company undertakes no obligation to publicly update or review any forward-looking statement, whether as a result of new information, future developments or otherwise, except as required by law. New risks and uncertainties may emerge from time to time, and it is not possible for the Company to predict their occurrence or how they will affect the Company. The Company qualifies all forward-looking statements by these cautionary statements.

Investor Relations:
Joseph Caminiti
[email protected]
312-445-2870 

Nvidia CEO Jensen Huang. Bloomberg/Getty Images Nvidia's AI ambitions are officially out of this world this year, and they haven't come back down to Earth.

The AI chip giant is adding to the team behind Space-1, its first computing system designed for space. In recent weeks, the chip giant posted a second job tied to orbital data centers.

The role — for a system software principal architect — will help build software for Space-1, which the chip giant unveiled at its GTC event in March.

Space data centers have emerged as a potential way to get around growing constraints on land, power, and cooling on Earth. Companies like SpaceX are racing to make the idea a reality, while skeptics argue the costs still outweigh the benefits.

During a recent earnings call, Nvidia CEO Jensen Huang said the economics around space computing are poor today but will improve over time.

The principal architect job post follows another role shared earlier this year for an orbital data center system architect. While that position focuses on designing the overall system — from computing hardware to satellites to connectivity systems — the new post focuses on making Space-1's software work in practice.

The person hired will design the software that runs the system so it can withstand radiation and extreme temperature swings and be managed remotely.

Space-1 harnesses Nvidia's latest Vera Rubin AI chip platform and is designed for low-Earth orbit missions.

The system software role requires previous experience building AI infrastructure and systems in space. It offers a base salary of $272,000 to $431,250, which doesn't include Nvidia's coveted equity awards.

While the technology is still in its early stages, Nvidia's latest job postings suggest the chipmaker is moving from conceptual planning to building the systems needed to make it work.

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Geoff Weiss is a senior reporter on Business Insider’s tech team, where he writes about AI startups and Y Combinator, the intersection of AI and the media industry, and workplace dynamics within top AI labs and chip companies.Previously, Geoff was on the media desk, covering YouTube and Netflix, and themes like the intersection of Hollywood and the creator economy. His work on Netflix’s video podcasting ambitions and Mr Beast’s lessons for Hollywood won second and first prize, respectively, at the 2025 LA Press Club Awards.Prior to joining Business Insider, Geoff was the senior editor of Tubefilter and a staff writer at Entrepreneur. He graduated from New York University with a degree in English Literature.He can be reached at [email protected], on Signal @geoffweiss.25, and on LinkedIn. Have a tip? Use a personal email address and a nonwork device; here's our guide to sharing information securely.Selected stories:Nvidia crushed its quarter — and CEO Jensen Huang said in a leaked all-hands that 'the market did not appreciate it'Nvidia will foot the bill for Trump's new visa fees. Here's what CEO Jensen Huang told staff.Massive AI salaries and RTO are fueling a real estate boom in San Francisco: 'It's going to rain money'The AI talent wars are ricocheting across startups. Here's how they're competing with Big Tech.

AI Space Big Tech More Data Centers Jobs

Shortly after the launch of ChatGPT in late November 2022, big tech hyperscalers realized that chipsets known as graphics processing units (GPUs) could be used to develop next-generation applications in artificial intelligence (AI). At the time, Nvidia (NVDA 1.42%) had a first-mover advantage in the GPU landscape. As a result, the company's revenue skyrocketed to record levels seemingly overnight -- as did its valuation.

After rapid and sustained share price appreciation, Nvidia quickly entered the trillion-dollar club. With a market capitalization of $4.7 trillion, Nvidia now sits at the top of this exclusive roster.

While GPUs have ushered in Nvidia's status as the world's most valuable company, I think its next trillion-dollar opportunity lies elsewhere. Luckily, Nvidia CEO Jensen Huang has given us some clues. Let's explore where Nvidia has been investing lately, and assess what these moves could mean for the company's trajectory as the AI infrastructure era takes shape.

Image source: Nvidia.

Understanding the critical role of AI networking AI networking refers to the specialized interconnects that link GPU clusters inside data centers. Without extremely high bandwidth, ultra-low latency, and lossless performance, communication among model training and inference deployments creates congestion that leaves GPUs underutilized.

This results in diminished returns on multi-billion-dollar hardware investments. In this sense, networking can be seen as being as important as raw compute. In other words, the fastest GPUs ultimately deliver little value if data cannot flow efficiently between clusters. As models grow larger and applications become more complex, the underlying network stitching AI development together becomes the limiting factor for overall system performance.

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Does Nvidia even offer AI networking solutions? While its GPU business takes the spotlight, Nvidia has quietly assembled deep expertise across multiple networking technologies tailored for AI.

The company's InfiniBand platform offers ultra-low latency, in-network computing, and high-bandwidth connectivity optimized for high-performance computing (HPC) and AI workloads. Nvidia complements this with its Spectrum family of Ethernet switches -- particularly the AI-optimized Spectrum-X platform, which features adaptive routing, congestion control, and predictable behavior within standard Ethernet environments.

Rounding out the offering are the BlueField data processing units (DPUs), which offload networking, storage, and security tasks from CPUs and GPUs. Taken together, Nvidia's networking suite forms a comprehensive, high-performance foundation capable of powering hyperscale AI deployments.

Nvidia is partnering with several AI networking leaders To accelerate its position and secure additional supply in the networking domain, Nvidia has made several targeted strategic investments.

In March, Nvidia invested $2 billion each in Coherent and Lumentum. The rationale behind these partnerships is to advance Nvidia's position in optical interconnects and silicon photonics, two essential layers for transmitting data at high speeds over long distances with lower power consumption. Nvidia invested another $2 billion in Marvell Technology to deepen its reach in designing custom AI accelerators.

These moves are far from random. Rather, each investment quietly strengthens Nvidia's ability to build end-to-end optical and electrical networking components layered atop its GPU ecosystem.

By combining its GPUs' architectures with an expanding networking portfolio, Nvidia is positioning itself as the key provider of complete AI factories -- integrated systems that capture compute, high-speed interconnects, DPUs, software, and advanced photonics. The goal is to enable customers to deploy turnkey infrastructure capable of training and running the largest AI models at unprecedented scale and efficiency.

From a valuation standpoint, Nvidia currently trades at a forward price-to-earnings (P/E) ratio of roughly 22. As the chart illustrates, this multiple sits well below the elevated levels Nvidia reached during the peak enthusiasm of the AI revolution's initial GPU phase.

NVDA PE Ratio (Forward) data by YCharts.

I don't think the market has fully incorporated Nvidia's expansion into networking. Since all signs point to an acceleration in AI infrastructure spending over the next several years, Nvidia's true earnings power could prove considerably larger than current expectations. Given these dynamics, I see Nvidia as a no-brainer stock to buy and hold, as hyperscalers bolster their capex budgets, allocating more to networking gear to meet their capacity needs.

Nvidia is the most valuable company in the world, with a market cap of more than $4.7 trillion. It has become not just an earnings powerhouse for its investors, but also for its partners.

Last fall, Nokia (NOK 7.26%) inked a $1 billion partnership to develop an AI-enabled cellular phone network, called AI RAN, or radio access network. It will essentially result in the upgrade to 6G communications and AI capabilities for mobile networks, transforming cell towers into data centers and changing mobile communications.

For its part, Nvidia is providing the AI chips and platform on which the AI RAN 6G platform will run.

Image source: Getty Images.

As part of the deal, Nvidia will deploy Nokia's switches, SR Linux software, and optical technologies at its data centers.

At the time the deal with Nokia was announced, Nokia was trading at just $6 per share, and had been in penny stock territory a few weeks prior at $4.90 per share. Since then, Nokia stock has skyrocketed 133% to almost $14 per share, including a 114% gain year to date.

The company is anticipating a major surge in revenue from the partnership, which has created investor excitement and bolstered its stock price.

Should you go all-in on Nokia? Nokia's stock price shot up following its first-quarter earnings release on April 23. The enthusiasm was less about its results, which were solid but not spectacular, and more about its outlook.

Nokia raised its guidance for the fiscal year. It's now calling for network infrastructure sales growth of 12% to 14% this fiscal year, up from 6% to 8% projected growth in January. The jump is based on the assumption that IP and optical networks revenue will grow 18% to 20% in 2026. The previous target was 10% to 12% growth. That increase in the outlook is related largely to the data center partnership with Nvidia.

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The other piece of the deal, the 6G networking, will have a longer runway, with earnings accretion from the partnership likely starting to emerge in 2027 and for several years after as the 6G networks get built.

So, this could be a transformative partnership for the beaten-down telecommunications stock, which has been trading mostly in penny stock range for more than a decade.

The recent surge has increased Nokia's price-to-earnings (P/E) ratio to 86 with a forward P/E of 36, so it's still a bit pricey. Analysts are mixed on the stock, with about half rating it as a buy with a $12 per share median price target.

While the future looks brighter for Nokia, investors may want to be cautious and pick their spots, given the recent rapid surge in Nokia's price and valuation. It does appear to be a long-term grower, but investors may want to find a better entry point.

The NVIDIA logo in this illustration taken June 11, 2026. REUTERS/Dado Ruvic/Illustration/File Photo Purchase Licensing Rights, opens new tab

SYDNEY, June 29 (Reuters) - Australian AI infrastructure company Firmus Technologies said on Monday it had signed a strategic partnership with Nvidia Corp (NVDA.O), opens new tab to help ​provide emerging AI firms with more cost-effective access to ‌computing power.

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Firmus said the deal would see it buy Nvidia infrastructure and sell Nvidia‑powered cloud services to "AI Native" customers, among others, in an agreement that would earn the ​U.S.-listed chip giant product revenue and a share of cloud ​revenue.

The deal will deliver 170,000 Graphics Processing Units (GPU) from ⁠the first quarter of 2027 to the start of 2028, that ​will be located in Batam, Indonesia.

Firmus said it expected to earn ​up to $30 billion in revenue during the first six years of the deal, based on customer commitments.

The Australian-founded company said the deal would make it easier for ​smaller and developing AI firms to access the technology's infrastructure.

"We ​have worked to figure out how to close the gap between the cost benefits ‌that ⁠the large guys have access to, which they do because they have great credit ratings, and the guys that are up and comers," Firmus co-chief executive Tim Rosenfield told Reuters. "This is actually a really ​material way to ​level the ⁠playing field a little bit to give the next a chance to compete with the big guys."

Nvidia ​has participated in Firmus' previous capital raisings making it ​an ⁠investor in the Australian firm, according to Firmus.

Firmus said in April it had raised $1.35 billion over the previous six months, giving it a $5.5 billion post-money valuation. ⁠It ​has appointed investment banks to work on ​a potential initial public offering, according to people familiar with the matter.

Rosenfield declined to ​comment on Firmus' IPO preparations.

Reporting by Scott Murdoch; Editing by Kate Mayberry

Our Standards: The Thomson Reuters Trust Principles., opens new tab

Scott Murdoch has been a journalist for more than two decades working for Thomson Reuters and News Corp in Australia. He has specialised in financial journalism for most of his career and covers the Australian financial services sector and superannuation. He is based in Sydney.