Nvidia Delivers: AI Anxiety Pauses, Fundamentals Still Soaring

比推Published on 2026-02-26Last updated on 2026-02-26

Abstract

NVIDIA delivered a blockbuster Q4 FY2026 earnings report, with revenue surging 73% year-over-year to a record $68.1 billion, significantly exceeding analyst expectations. This performance, described as "explosive," served to temporarily alleviate market anxieties about an AI bubble, demonstrating that demand for computing power remains robust. Key highlights include Data Center revenue growing 75% to $62.3 billion, driven by strong demand for AI compute. Within this segment, Compute revenue rose 58%, while Networking revenue skyrocketed 263%, reflecting the success of NVLink technology. The company's non-GAAP gross margin climbed to 75.2%, a new high, attributed to improved product mix with the new Blackwell architecture and reduced inventory charges. For Q1 FY2027, NVIDIA provided a revenue guidance of $78 billion (±2%), which implies a nearly 77% year-over-year growth rate. This forecast notably excludes data center compute revenue from China. CEO Jensen Huang stated that the company is on track to surpass its $500 billion annual revenue target, with supply is expected to meet demand through next year. He emphasized that customer investment in AI computing is accelerating, and enterprise adoption of AI agents is soaring. Despite the strong results and guidance, the stock experienced volatility after the earnings call, with some analysts noting that high operating expenses and a change in accounting—where stock-based compensation (SBC) will no longer be excluded from non-...

Author: Li Dan, Wall Street Insights

Original Title: Cooling AI Anxiety! Nvidia's Q4 Earnings Report is the Best "Tranquilizer"

Amid recent product releases from Anthropic and Citrini's "Doomsday Report" heightening investor anxiety, the artificial intelligence (AI) boom faced a direct test. Nvidia delivered "blockbuster" performance, proving that the demand generated by AI remains robust.

On Wednesday, US Eastern Time, February 25th, Nvidia announced that for the fourth quarter ("Q4") of fiscal year 2026, ended January 31, 2026, revenue reached a record $68.1 billion, a year-over-year increase of approximately 70%. The core business, data centers, which contributes over 90% of revenue, also set a new single-quarter record, exceeding analyst expectations by over 3%.

Nvidia's profitability in Q4 was equally strong. On a non-GAAP basis, adjusted earnings per share (EPS) grew over 80% year-over-year, about 5.9% higher than analyst expectations. The gross margin also climbed beyond expectations to 75.2%, a new high in the past year and a half.

Even more encouraging for investors was that Nvidia's guidance for the first quarter of fiscal year 2027 (Q1) was also stronger than expected. Revenue is expected to reach another new high, with the midpoint of the guidance range being 7.1% higher than the analyst consensus expectation midpoint, and even 4% higher than the buyers' optimistic expectations. The year-over-year growth rate accelerated to nearly 77% compared to Q4. Nvidia pointed out that this guidance excludes data center compute revenue from the China market.

During the earnings call on Wednesday, Nvidia CEO Jensen Huang also raised the chip revenue forecast made previously, stating, "We will surpass the $500 billion target." Supply will meet demand through next year. At the GTC conference last October, Huang revealed that Nvidia had secured a total of $500 billion worth of chip orders for calendar years 2025 and 2026, including the next-generation Rubin chips set to begin mass production this year.

Huang stated that customers are racing to invest in AI computing. Computing demand is growing rapidly. Enterprise adoption of agents is soaring. Speaking about the "space data center," he said the current space data center economy is still "impoverished," but the situation will change over time.

After the earnings release, Nvidia's stock price, which had already risen over 1% on Wednesday, extended its gains after hours, with the increase quickly expanding to once exceed 4%. Analysts believe the key to the market's buying lies in: Data center revenue and total revenue both exceeding expectations; The gross margin continues to improve with the production ramp of the new Blackwell architecture chips, and the guidance for this quarter is even stronger without including part of the China market revenue, reinforcing the narrative of resilient AI computing demand.

However, during the conference call, Nvidia's stock price continued to give back gains, turning negative after hours, once falling over 1%. Some commentary stated that the stock price decline shows investors were not impressed by the latest guidance,暗示ing that market concerns about an overheated AI economy will continue to trouble Nvidia. Other analysis pointed out that operating expenses continue to grow at a high rate, and stock-based compensation (SBC) will be included in non-GAAP metrics starting from Q1, which may short-term change investors' perception of "profit acceleration."

Q4 Revenue Hits Single-Quarter Record High, Gross Margin Reaches New High in a Year and a Half

Nvidia's Q4 revenue grew 73% year-over-year to $68.127 billion, with growth rate significantly higher than the previous quarter's 62%, exceeding Nvidia's own guidance midpoint of $65 billion. Analyst expected revenue was $65.91 billion,约68% year-over-year growth. Nvidia's full-year revenue also reached an annual record of $215.938 billion, a 65% increase compared to the previous year.

Gross margin was another highlight in Q4: The non-GAAP gross margin was 75.2%, up 1.7 percentage points year-over-year and 1.6 percentage points quarter-over-quarter, setting a new single-quarter high since Q2 of fiscal year 2025, higher than the analyst consensus expectation of 74.7% and the optimistic expectation of 75.0%.

Nvidia's Chief Financial Officer (CFO) Colette Kress explained that the year-over-year improvement in gross margin came from "reduced inventory charges," while the sequential improvement was related to the "better product mix and cost structure" brought by the continued volume production of Blackwell chips.

However, for the entire fiscal year 2026, the non-GAAP gross margin declined, dropping from 75.5% in the previous fiscal year to 71.3%, a decrease of 4.2 percentage points year-over-year, showing that during the platform transition and supply ramp phase, the full-year profit margin will still be affected by structural disruptions.

Data Center: Compute Growth Steady, Networking Accelerates

Nvidia's data center business recorded revenue of $62.314 billion in Q4, a 75% year-over-year increase, with acceleration higher than the previous quarter's 66%. Analysts expected约70% year-over-year growth to $60.36 billion.

Within the data center, Nvidia provided two sets of numbers worth noting:

  • Data Center Compute revenue was $51.334 billion, a 58% year-over-year increase, with acceleration higher than Q3's 56%.

  • Data Center Networking revenue was $10.980 billion, a 263% year-over-year increase, with acceleration far exceeding Q3's 162%.

Nvidia attributed the explosion in networking revenue to: The "launch and continued ramp" of NVLink compute fabric for GB200 and GB300 systems, alongside continued growth in Ethernet and InfiniBand platforms.

In other words, the market should not only focus on the shipment节奏 of GPUs themselves, but also see that Nvidia is packaging "compute, interconnect, systems" into a more irreplaceable overall solution. The high growth rate of networking revenue is precisely the financial reflection of this strategy.

Regarding customer structure, the company disclosed: In Q4, revenue from hyperscalers accounted for略超50% of total data center business revenue, still the largest customer category, but revenue growth in the quarter came more from other data center customers, showing that revenue sources are diversifying, marginally alleviating concentration risk.

Blackwell Drives Gaming Demand, Short-Term Impacted by Supply and Channel Disruptions

Nvidia's gaming business revenue in Q4 was $3.727 billion, a 47% year-over-year increase. Analyst expectations were $4.01 billion. The previous quarter saw 30% year-over-year growth.

The gaming business's year-over-year growth accelerated in Q4. Nvidia explained this was primarily driven by strong demand for Blackwell chips. However, this business's revenue decreased 13% sequentially, due to "natural channel inventory drawdown after the holiday season." Notably, Nvidia explicitly提示: Starting in Q1 and beyond, supply constraints are expected to become a headwind for the gaming business.

Q4 professional visualization revenue was $1.321 billion, a 159% year-over-year increase. Analyst expectations were $770.7 million. The previous quarter saw 56% year-over-year growth.

Professional visualization also achieved more than double year-over-year revenue growth and 74% sequential growth under Blackwell's impetus, becoming one of the brightest incremental businesses besides data centers. However, the scale of this business is far smaller than data centers.

Q1 Revenue Guidance Midpoint Implies ~77% YoY Growth, Excluding China Data Center Compute Revenue

Regarding performance guidance, Nvidia announced that Q1 revenue is expected to be $78.8 billion, plus or minus 2%, i.e., $76.44 billion to $79.56 billion. This range implies that Nvidia's revenue this quarter will刷新the record high set in Q4.

Calculated based on the revenue guidance midpoint, this implies Nvidia expects Q1 revenue to grow 76.9% year-over-year, further accelerating from Q4's 73% growth rate.

Nvidia's revenue guidance midpoint not only exceeded the analyst consensus expectation midpoint of $72.78 billion but also surpassed the buyers' optimistic expectation of $74 billion to $75 billion.

Nvidia's Q1 gross margin is in line with Wall Street buyers' optimistic expectations and is expected to set a new high since Q2 of fiscal year 2025.

The non-GAAP adjusted gross margin for Q1 is expected to be 75%, plus or minus 50 basis points, i.e., 74.5% to 75.5%. The buyers' optimistic expectation was 75%, and the sell-side consensus expectation was 74.7%.

Non-GAAP to Include Stock-Based Compensation Starting Q1

Simultaneously with the earnings release, Nvidia announced that starting from Q1, financial metrics on a non-GAAP basis will no longer exclude stock-based compensation (SBC). Due to this adjustment, Nvidia预计that non-GAAP operating expenses in Q1 will be impacted by approximately $1.9 billion.

This change will directly alter the "customary口径" long used by the market for横向comparing profit margins and expense ratios. It may necessitate recalibration of consensus models in the short term and will also allow investors to see more clearly the real costs Nvidia incurs to maintain talent and R&D leadership.

Twitter:https://twitter.com/BitpushNewsCN

Bitpush TG Discussion Group:https://t.me/BitPushCommunity

Bitpush TG Subscription: https://t.me/bitpush

Original Link:https://www.panewslab.com/zh/articles/019c982d-28b7-75ea-bc74-9865e5f16ce0
Disclaimer: All articles on Bitpush represent the author's views and do not constitute investment advice.
Related News
    No related articles

Related Questions

QWhat was NVIDIA's revenue for Q4 of fiscal year 2026, and how did it compare to analyst expectations?

ANVIDIA's revenue for Q4 of fiscal year 2026 was a record $68.1 billion, a 73% year-over-year increase. This exceeded analyst expectations of $65.91 billion and the company's own guidance midpoint of $65 billion.

QWhich segment was the primary driver of NVIDIA's revenue growth in Q4, and what were its key components?

AThe Data Center segment was the primary driver, with revenue of $62.314 billion, a 75% year-over-year increase. Its key components were Compute revenue ($51.334 billion, up 58%) and Networking revenue ($10.980 billion, up 263%), driven by demand for AI computing and NVLink solutions.

QWhat is NVIDIA's revenue guidance for Q1 of fiscal year 2027, and what notable exclusion does it contain?

ANVIDIA's revenue guidance for Q1 is $78.0 billion, plus or minus 2%. This implies a year-over-year growth of nearly 77%. The company specifically noted that this guidance does not include Data Center compute revenue from the China market.

QHow did NVIDIA's non-GAAP gross margin perform in Q4, and what factors contributed to its improvement?

AThe non-GAAP gross margin was 75.2% in Q4, a 1.7 percentage point year-over-year increase and a 1.6 percentage point sequential increase, reaching a new high for the past year and a half. The improvement was attributed to reduced inventory charges and a more favorable product and cost structure from the ongoing ramp of the new Blackwell architecture.

QWhat significant accounting change did NVIDIA announce alongside its earnings, and what is its expected impact?

ANVIDIA announced that starting in Q1 of fiscal year 2027, its non-GAAP financial metrics will no longer exclude stock-based compensation (SBC). This change is expected to increase non-GAAP operating expenses by approximately $1.9 billion for Q1, providing a clearer view of the real costs of retaining talent and R&D leadership.

Related Reads

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

Silicon Valley investor and "Godfather of Startups" Steve Hoffman warns that combining Web3 with AI is likely a trap, not a promising venture. In an interview, Hoffman argues that while AI is a foundational technology touching all industries, Web3 adds complexity, friction, and regulatory risk without solving mainstream consumer or business needs. He advises founders to focus on deep, specialized applications where startups can out-iterate giants, rather than on generic features easily replicated by large tech companies. Hoffman observes that Silicon Valley will lead foundational AI research, while China excels at rapid, large-scale application and commercialization, particularly in robotics. He stresses that AI-driven autonomous agents capable of collaborative, multi-step tasks are 2-4 years away, which will cause significant job displacement. The solution is not to slow AI but to redesign business models around human-AI collaboration and reform social systems like education and retraining. For startups, Hoffman recommends focusing on vertical, expertise-heavy domains to build defensibility. He sees major opportunities in AI fraud detection and cybersecurity. Key founder mindsets include systemic thinking over feature-focus, relentless customer centricity, building adaptive teams, and deeply understanding AI's capabilities and limits. Hoffman is also leading a non-profit initiative to establish university centers aimed at training future leaders in responsible, human-value-aligned AI innovation.

marsbit1h ago

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

marsbit1h ago

Token Inefficient, Economy Tokenless

The article "Tokens Aren't Economical, Economics Aren't Tokenized" analyzes a pivotal shift in the AI industry from a technology-driven narrative to one dominated by capital efficiency. It highlights two concurrent trends: a severe capital shortage due to the exorbitant and recurring costs of compute (e.g., OpenAI's high burn rate) and a wave of corporate spin-offs where major tech companies are separating their AI units (like Kuaishou's Kling and Baidu's Kunlunxin). The core argument is that AI's "anti-internet" business model, where user growth increases costs rather than profits, has created a disconnect between high valuations and actual cash flow. Spin-offs address this by allowing AI assets to be valued independently. Within a parent company, they are seen as cost centers, but as standalone entities, they are priced based on their growth potential and scarcity in the primary market, leading to massive valuation premiums (e.g., Kling's estimated value tripling post-spin-off). The industry is at an inflection point, moving from "model worship" to "value realization." The competition is evolving from a pure compute (GPU) race to a broader focus on systemic efficiency and full-stack engineering (involving CPUs and orchestration) to achieve viable commercialization. The year 2026 is framed as a critical moment where the industry must definitively answer how to economically translate AI capability into tangible business value, reshaping the sector's future power structure.

marsbit1h ago

Token Inefficient, Economy Tokenless

marsbit1h ago

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

In 2026, a historic shift occurred in AI as major cloud providers' inference spending surpassed training spending for the first time, signaling a move from "building large models" to "using large models." This shifts the core challenge from computing power to the "memory wall"—the bottleneck of data movement (model weights, activations, KV Cache) between external DRAM and processors, where energy and latency from data transfer far exceed computation itself. Companies like Nvidia face GPU idle time due to bandwidth limits. In contrast, Cerebras Systems adopts a radical "wafer-scale" approach with its Wafer-Scale Engine (WSE). Instead of cutting a silicon wafer into many chips, Cerebras uses almost the entire wafer as one massive chip (WSE-3). This design provides 44GB of on-chip SRAM, delivering memory bandwidth thousands of times higher than traditional HBM (e.g., 21 PB/s vs. Nvidia B200). For LLM inference, weights are streamed layer-by-layer from external MemoryX storage to the chip, avoiding HBM bottlenecks. This results in token generation speeds 1.5–5 times faster than Nvidia's B200 in some models and significant advantages in first-token latency and long-context tasks. Additionally, Cerebras's architecture offers much lower interconnect power consumption (0.15 pJ/bit vs. GPU's ~10 pJ/bit). However, Cerebras faces challenges: SRAM scaling has slowed with advanced nodes, limiting future capacity gains; the chip requires specialized liquid cooling and custom software stacks; and its external I/O bandwidth (150 GB/s) is low compared to NVLink, hindering multi-system scaling for very large models. Competition is intensifying. Major players are pursuing three paths: 1) Developing proprietary inference ASICs (e.g., Google TPU, Microsoft Maia), 2) Leveraging advanced packaging (e.g., TSMC's SoW) to democratize wafer-scale-like integration, potentially eroding Cerebras's process advantage within a few years, and 3) Exploring optical interconnects for ultimate bandwidth. Commercially, Cerebras is transitioning from a hardware vendor to a service provider, facing the immense challenge of building high-power, specialized data centers to meet large contracts (e.g., 250MW/year from 2026–2028). In conclusion, the AI inference era presents a fundamental architectural trade-off. Cerebras opts for extreme physical optimization for low-latency, single-task performance, while Nvidia prioritizes versatility and massive cluster throughput. The path forward remains uncertain, with technology and business models still evolving in the race toward advanced AI.

marsbit1h ago

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

marsbit1h ago

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

**Title: Has Bitcoin's Rebound Ended, Entering the Late Bear Market Phase?** **Summary:** Bitcoin's price has declined by 13% this week, signaling a potential return to late-stage bear market conditions. The price fell to around $67k, positioned between the Realized Price and Realized Cap Weighted Average. For the first time since early 2022, the Short-Term Holder cost basis has dropped below this key average, confirming a hallmark of late-cycle bear markets. Profitability metrics have collapsed sharply. The 7-day average of the Realized Profit/Loss ratio plummeted from a local high of 3.16 to 0.29, mirroring the February panic sell-off. Critically, the 90-day average never breached the threshold of 2, indicating the recent rally to $82k was a bear market bounce, not a structural shift. Realized losses surged to $1.35 billion daily, with $770 million coming from Long-Term Holders selling at a loss. This accelerating redistribution of supply from weak to strong hands is a necessary but ongoing process for a market bottom. The rally stalled almost precisely at the aggregate cost basis (~$83k) of US spot Bitcoin ETF investors, turning that level into strong resistance and leaving the average ETF holder underwater again. Spot market flows have turned decisively negative, showing sellers are dominating order books despite the price drop. While a significant futures long liquidation event cleared over $400 million in leverage, providing a potential reset, sustained spot demand is yet to materialize. Options markets continue to price in higher future volatility (Implied Volatility) than recent price action (Realized Volatility) has shown, with a persistent skew towards put options, indicating ongoing demand for downside protection. In conclusion, multiple metrics point to a fragile market structure. Resistance at the ETF cost basis, accelerating realized losses, dominant spot selling, and cautious options pricing all suggest the bear market trend persists. A sustainable recovery likely requires a resurgence of spot demand, ETF holders returning to profit, and a clear reduction in selling pressure.

marsbit1h ago

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

marsbit1h ago

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

In today's TechFlow Intelligence Briefing, several major tech stories highlight a growing theme of trust and credibility gaps across AI, crypto, and finance. AI company Anthropic has publicly called for a global pause in AI development, citing risks from Claude's "recursive self-improvement." Ironically, this coincides with reports the company is preparing for a massive IPO targeting a near $1 trillion valuation. This perceived hypocrisy, coupled with widespread user complaints about Claude's declining performance, is sparking debate over whether the safety warning is genuine or a competitive tactic. Meanwhile, in a substantive security move, Anthropic open-sourced a framework for AI-powered vulnerability discovery. In the crypto market, Bitcoin's price drop below $61,000 triggered over $1.16 billion in liquidations, flipping the market into a state where more BTC is held at a loss than at a profit, a historical bearish signal. On the corporate front, SpaceX's highly anticipated IPO is generating immense Wall Street excitement, with Goldman Sachs projecting 100x revenue growth by 2030. However, the S&P 500 has refused to fast-track the company's inclusion post-IPO, potentially limiting immediate institutional demand. Separately, ByteDance's AI app Doubao lost over 6 million monthly active users after introducing a subscription model, highlighting the challenges of AI monetization. Other notable developments include Nvidia certifying HBM4 memory from Samsung, SK Hynix, and Micron; Cloudflare's acquisition of front-end tooling company VoidZero; and its CEO warning that bot traffic now exceeds human traffic online. The underlying narrative connects these events: a trust crisis. From AI firms' contradictory actions and crypto volatility to the clash between SpaceX's hyped narrative and institutional rules, a pattern is emerging where stated intentions and actual practices are increasingly misaligned.

marsbit1h ago

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

marsbit1h ago

Trading

Spot
Futures

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of AI (AI) are presented below.

活动图片

Top Questions

Hot Categoriesright-arrow

Hot Tagsright-arrow