Nvidia Corporation (NASDAQ: NVDA) remains the central character in the AI boom — and on December 3, 2025, its stock is trading around the $181 level after a volatile few weeks. The company sits near a $4.4 trillion market capitalization, making it one of the most valuable companies in the world and a core holding for many investors exposed to artificial intelligence. [1]
Today’s narrative around Nvidia stock is shaped by three big themes:
- A $100 billion OpenAI megadeal that the CFO now confirms is still not finalized. [2]
- A $2 billion strategic investment in Synopsys that tightens Nvidia’s grip on AI chip design tools. [3]
- Mounting competition from Alphabet’s custom AI chips (TPUs), which could ultimately threaten a slice of Nvidia’s data-center revenue. [4]
At the same time, Wall Street still rates NVDA a “Strong Buy” with average 12‑month price targets roughly 35–45% above the current share price, even as some valuation models argue the stock is expensive. [5]
Below is a detailed look at Nvidia’s stock, news and forecasts as of December 3, 2025, suitable for Google News and Discover.
Nvidia Stock Price Today and Recent Performance
- Latest price: NVDA is trading around $181 per share, with intraday moves between roughly $179 and $182 on December 3. [6]
- 52‑week range: About $86.62 (low) to $212.19 (high), highlighting just how explosive the last year has been — and how sharp the recent pullback from October’s record highs looks. [7]
- 12‑month performance: Over the past year, Nvidia shares are up roughly 25%, outpacing the broader market but lagging some other AI‑linked names after the recent correction. [8]
- Valuation snapshot: Most data providers now peg Nvidia’s trailing P/E ratio around 44–46, down from prior extremes but still well above the semiconductor industry median near the mid‑30s. [9]
In other words, Nvidia is no longer at the euphoric valuation levels it reached earlier this year, but the stock still embeds very high expectations for AI growth and profitability.
Today’s Key Headlines for Nvidia (December 3, 2025)
1. The $100 Billion OpenAI Megadeal Is Still Not Signed
At the UBS Global Technology and AI Conference, Nvidia CFO Colette Kress confirmed that the widely discussed $100 billion infrastructure deal with OpenAI has not yet been finalized and remains based on a letter of intent. [10]
Key points from her remarks, reported by several outlets:
- The plan contemplates deploying Nvidia systems equivalent to ~10 gigawatts of data‑center capacity over several years to power OpenAI’s next‑generation models. [11]
- None of those potential GPU shipments are included in Nvidia’s existing $500 billion in booked chip sales through 2026, meaning current backlog is already massive without OpenAI. [12]
- Kress also addressed concerns about “circular investment”, where Nvidia invests in AI companies that then spend heavily on Nvidia hardware, saying the company is still evaluating structure and risk. [13]
Why it matters for the stock:
For bulls, this is optionality: a not‑yet‑booked mega‑contract that would sit on top of an already huge order book. For bears, the delay and the circular‑investment debate feed AI‑bubble worries and raise the risk that regulators or investors scrutinize Nvidia’s deal structures more closely.
2. $2 Billion Synopsys Deal Deepens Nvidia’s AI Design Moat
On December 1, Nvidia and Synopsys announced a major strategic partnership in which Nvidia will invest $2 billion in Synopsys common stock via a private placement at $414.79 per share. [14]
The agreement has two main pieces:
- Equity stake: Nvidia becomes a major shareholder in Synopsys, the market‑leading electronic design automation (EDA) company.
- Technology collaboration: The firms will jointly develop GPU‑accelerated design, simulation and verification tools, using CUDA‑powered computing to massively speed up chip and system design across industries, from semiconductors to automotive and advanced manufacturing. [15]
Initial market reaction saw Synopsys shares jump several percent and Nvidia gain around 1–3% as investors interpreted the move as:
- A way to pull more of the chip‑design workflow into Nvidia’s ecosystem, making its GPUs even more central to how next‑generation chips are created; [16]
- Another example of Nvidia spending its substantial cash flows on strategic equity partnerships rather than simply hoarding cash or raising the dividend. [17]
For Nvidia shareholders, the Synopsys deal is less about near‑term earnings accretion and more about moat‑building: if EDA tools are optimized first and best for Nvidia GPUs, rivals have an even tougher time unseating the company in high‑end AI compute.
3. Alphabet’s TPUs: The Most Visible Threat to Nvidia’s Data‑Center Franchise
A growing share of today’s Nvidia coverage focuses on Alphabet’s tensor processing units (TPUs) and their potential to erode Nvidia’s near‑monopoly in AI accelerators.
Recent reports highlight that:
- Google is looking to sell TPUs to external customers, including discussions with Meta about multi‑billion‑dollar TPU purchases, rather than keeping the chips purely for internal use. [18]
- Analysts cited in these pieces estimate that such deals could eventually threaten around 10% of Nvidia’s annual revenue, if hyperscalers shift a slice of their AI workloads away from Nvidia GPUs. [19]
- Market commentary frames this as a shift from “Nvidia vs AMD” to “Nvidia vs the cloud giants’ in‑house silicon” — including Alphabet, Amazon (Trainium/Inferentia), Microsoft and Meta. [20]
Nvidia’s own response has been combative at times. A Reuters report describes how the company even issued a memo to analysts defending its business practices and technology leadership after a wave of critical notes and social‑media commentary, including from prominent investor Michael Burry. [21]
Investor takeaway:
TPUs and other in‑house accelerators are not an existential threat today — Nvidia’s ecosystem and CUDA software remain the default standard for AI training — but they are now a central risk factor baked into most professional forecasts for NVDA.
4. AI Infrastructure Surge Meets a Memory Supply Crisis
Nvidia sits at the heart of a broader scramble to build AI infrastructure:
- A Reuters deep‑dive published today details how the AI frenzy is driving an acute global shortage of memory chips, particularly the high‑bandwidth memory (HBM) that feeds Nvidia’s top‑end GPUs. [22]
- Memory suppliers such as SK Hynix, Samsung and Micron have seen inventory levels crash and prices more than double in some segments, with SK Hynix telling analysts that shortages could last through late 2027. [23]
- The same piece notes that Nvidia and OpenAI are among the companies whose voracious demand for AI infrastructure helped divert capacity away from more traditional memory products, inadvertently contributing to the crunch. [24]
In parallel, Nebius, a fast‑growing European “neocloud” provider, is aggressively expanding AI data centers across the US and Europe using Nvidia‑powered GPU clusters, backed by $17 billion in Microsoft contracts and $3 billion from Meta. [25]
Meanwhile, Amazon Web Services is rolling out “AI Factories” that transform customer data centers into high‑performance AI environments, further underscoring insatiable demand for AI compute. [26]
For Nvidia investors, this is a double‑edged sword:
- Bullish: Demand for AI compute and memory is so strong that suppliers are sold out well into 2026, reinforcing the idea of a multi‑year AI capex super‑cycle. [27]
- Risk: If memory shortages delay new AI projects or make data centers uneconomical, some of Nvidia’s most aggressive growth assumptions could be pushed out — or, in a bubble scenario, never fully realized.
5. AI Robotics Expansion and Sentiment Tailwinds
Beyond data centers, Nvidia is also leaning into AI robotics and startup ecosystems:
- A December 3 article from Meyka highlights Nvidia’s new London facility for AI robotics startups, part of a broader plan to incubate next‑generation robotics and automation solutions built on Nvidia platforms. [28]
- The piece notes that investors, including those in Japan, are watching these initiatives closely as the robotics‑plus‑AI theme gains momentum across manufacturing, healthcare and autonomous systems. [29]
On the sentiment side, Elon Musk recently named Google and Nvidia as his two favorite AI investments in a November 30 podcast, calling Nvidia’s AI chip dominance “obvious” as a driver of future value. [30]
While celebrity endorsements are not a fundamental driver, they help keep Nvidia top‑of‑mind for retail investors and reinforce its status as a flagship AI stock.
Nvidia’s Fundamentals: Q3 FY2026 Earnings and Backdrop
Nvidia’s most recent results, for fiscal Q3 2026 (quarter ended October 26, 2025), were nothing short of massive:
- Revenue:$57.0 billion, up 22% quarter‑over‑quarter and 62% year‑over‑year.
- Data center revenue:$51.2 billion, up 25% Q/Q and 66% Y/Y, underscoring Nvidia’s dominance in AI infrastructure. [31]
- Gross margins: Around 73–74% on both a GAAP and non‑GAAP basis, among the highest in large‑cap tech. [32]
- EPS: GAAP and non‑GAAP diluted EPS of $1.30, up roughly two‑thirds from the prior year. [33]
- Guidance: Nvidia guided for Q4 revenue around $65 billion (±2%), well ahead of consensus estimates in the low $60 billions at the time. [34]
Management also highlighted:
- An AI “virtuous cycle,” where better models drive more compute spending, which in turn enables even better models, especially around its Blackwell GPU platform. TS2 Tech+1
- More than $37 billion returned to shareholders via buybacks and dividends in the first nine months of FY2026, with $62.2 billion still approved for repurchases, reflecting enormous free‑cash‑flow generation. TS2 Tech+1
However, Nvidia’s trajectory hasn’t been free of turbulence:
- Earlier in 2025, export controls on high‑end AI chips to China forced Nvidia to take a $5.5 billion charge related to H20 inventory and reshuffle its product lineup, though subsequent quarters showed the company pivoting effectively toward US and allied markets. TS2 Tech+1
Fundamentally, Nvidia today is a high‑growth, high‑margin AI infrastructure powerhouse — but one that operates under significant geopolitical and competitive pressure.
Wall Street Forecasts for Nvidia Stock
Consensus Ratings and Price Targets
Across the major data providers, Nvidia still enjoys one of the strongest analyst profiles in big tech:
- StockAnalysis: 39 covering analysts rate NVDA a “Strong Buy”, with an average 12‑month price target around $248.64, implying roughly 38% upside from the current price. The target range runs from $100 to $352. [35]
- MarketBeat: Aggregating 54 analysts, the average target is about $258.65, with a high of $352 and a low of $205. This suggests about 43% upside from roughly $181 per share. [36]
- 24/7 Wall St.: Citing around 64 analysts, the site reports that 60 rate Nvidia a Buy, many with Strong Buy ratings, and notes a median one‑year target near $250–251, again implying close to 40% upside. [37]
Taken together, mainstream Wall Street still views Nvidia as a core AI winner with sizable upside over the next year, despite the recent drawdown and intense debate around valuation.
Morgan Stanley: “AI Hardware King” With a $250 Target
A closely watched note from Morgan Stanley this week reinforced that bullish stance:
- Analyst Joseph Moore increased his NVDA price target from $235 to $250, one of the highest on the Street, implying nearly 40% upside from recent prices. [38]
- After a tour of Asian markets and supply chains, the firm concluded that Nvidia’s competitive edge remains intact and that Chinese AI chip efforts are still limited in scale and sophistication relative to Nvidia’s platform. [39]
- Morgan Stanley also said it is comfortable with Nvidia’s long‑term goal of hitting $500 billion in annualized chip revenue, arguing that supply — not demand — is the main constraint through 2026. [40]
Longer‑Term Forecasts and Quant Models
- 24/7 Wall St. projects Nvidia could reach $170 billion in fiscal 2026 revenue, with the broader AI market growing at a mid‑30s% CAGR through 2030, underpinning long‑term optimism. [41]
- Quant and algorithmic models collected by various platforms generally forecast modest near‑term gains but leave room for very large upside scenarios by 2030 if Nvidia retains AI leadership and the AI capex cycle continues. [42]
At the same time, not every model agrees that Nvidia is cheap:
- A fair‑value estimate based on the Peter Lynch formula pegs intrinsic value at around $102 per share, implying more than 40% downside from today’s price. [43]
- By contrast, a DCF‑style intrinsic value model at AlphaSpread puts fair value closer to $208, framing Nvidia as about 13% undervalued. [44]
These wide disparities highlight how much hinges on uncertain long‑term assumptions about AI demand, margins and competition.
Bull vs. Bear Case for Nvidia Stock (As of December 3, 2025)
Bull Case: Why Optimists Still Love NVDA
- Dominant AI Data‑Center Platform
Nvidia controls the vast majority of the AI accelerator market in cloud data centers, with quarterly data‑center revenue now above $50 billion and still growing at more than 60% year‑over‑year. [45] - Exceptional Profitability and Cash Flow
With 70%+ gross margins, high net margins and tens of billions in buybacks, Nvidia has the financial firepower to invest aggressively in R&D, ecosystem partnerships (like Synopsys) and strategic equity stakes in key AI players. [46] - Software and Ecosystem Moat
Tools such as CUDA, cuDNN and Nvidia’s AI SDKs make its GPUs sticky. Cloud providers, enterprises and researchers have standardized on Nvidia’s platform, raising switching costs even if competing hardware becomes available. [47] - Product Roadmap and Innovation Pace
Blackwell GPUs are still ramping, and Nvidia is already talking up its Rubin (R100) generation, signaling an intent to continue leapfrogging rivals on performance and total platform capabilities. TS2 Tech+1 - AI Super‑Cycle Tailwind
Massive AI data‑center builds, the rise of neocloud providers like Nebius, and AWS’s AI Factories all suggest AI compute demand will keep expanding well into the second half of the decade. [48] - Expansion Beyond Core Data Centers
Nvidia is pushing into AI robotics, automotive and edge computing, including new robotics hubs and automotive partnerships, diversifying its long‑term revenue mix. [49]
Bear Case: Why Skeptics See Bubble Risk
- Rich Valuation and P/E in the Mid‑40s
Even after the pullback, Nvidia trades at roughly 45x trailing earnings and around 26x forward earnings, well above many peers. That leaves little room for disappointment if AI spending slows or competition pressures margins. [50] - Hyperscaler In‑House Chips (TPUs, Trainium, etc.)
Alphabet’s TPUs, Amazon’s Trainium/Inferentia and Microsoft/Meta’s internal silicon programs directly target the same AI workloads that Nvidia currently dominates. Some analysts believe these efforts could eventually siphon off double‑digit percentages of Nvidia’s future revenue. [51] - Geopolitics and Export Controls
US restrictions on high‑end AI chips to China have already forced a multi‑billion‑dollar H20 write‑down and could tighten further, while China pushes state‑backed projects toward domestic suppliers. TS2 Tech+1 - AI Bubble and Circular Financing Concerns
Critics, including Michael Burry and some research boutiques, argue that Nvidia’s large investments in AI startups and prospective deals like the OpenAI megaproject risk creating circular demand — with Nvidia‑funded entities ordering Nvidia hardware — which could deflate quickly in a downturn. [52] - Supply Chain and Memory Shortages
As Reuters notes, global memory shortages driven by AI demand may delay some data‑center projects and raise costs, potentially constraining the pace at which Nvidia can convert demand into revenue. [53]
In short, bulls see Nvidia as the operating system of the AI economy, while bears fear we are seeing a classic late‑cycle tech bubble with extreme concentration and sky‑high expectations.
What Today’s News Means for Nvidia Investors
As of December 3, 2025, Nvidia stock sits at a crossroads:
- The company just delivered record earnings and bullish guidance, remains deeply embedded in AI infrastructure and continues to expand its ecosystem through deals like Synopsys. [54]
- The OpenAI deal narrative has turned more nuanced: the opportunity is huge, but the details, timing and financial structure are still uncertain and subject to scrutiny. [55]
- Competition from Alphabet and other hyperscalers is no longer theoretical; TPUs and other in‑house accelerators are now central variables in any long‑term Nvidia valuation model. [56]
- Wall Street, for now, still leans firmly bullish, with Strong Buy ratings and price targets clustered around $250–260, though independent valuation models vary widely. [57]
For long‑term investors, the decision comes down to risk tolerance:
- Those who believe in a multi‑year AI super‑cycle, Nvidia’s ecosystem moat and its ability to navigate competition may view today’s valuation as justifiable, especially after the recent pullback from October highs.
- More cautious investors may focus on valuation, geopolitical risk and the possibility of an AI capex hangover, choosing to wait for better entry points or clearer evidence that hyperscaler in‑house chips will not meaningfully erode Nvidia’s economics.
Either way, Nvidia remains the defining stock of the AI era, and the developments of December 3, 2025 — from the OpenAI deal update to the Synopsys partnership and intensifying TPU competition — will shape how investors value NVDA heading into 2026.
Disclaimer: This article is for informational purposes only and does not constitute investment advice or a recommendation to buy or sell any security. Investors should conduct their own research or consult a licensed financial advisor before making investment decisions.
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