Fiscal 2028 revenue growth guided to ~70% on supply constraints
Guidance · revenue to $108B
NVIDIA reported a blowout quarter with 100% YoY revenue growth, but the stock face-planted on guidance for gross margins to crater to 71-72% in Q4 due to extreme memory price increases. Despite the margin pain, management guided to ~70% revenue growth in FY28, a number that is still supply-constrained, with unconstrained demand far higher. The call was dominated by massive multi-hundred-billion-dollar infrastructure buildouts and financial engineering (financing platforms, take-or-pay deals) aimed at funding 'compute-limited' AI labs. FY27 Q2 revenue was $96B ( YoY +100%), slightly above guidance, but Q3 guide of $108B came in just in line.
NVIDIA reported a blowout quarter with 100% YoY revenue growth, but the stock face-planted on guidance for gross margins to crater to 71-72% in Q4 due to extreme memory price increases. Despite the margin pain, management guided to ~70% revenue growth in FY28, a number that is still supply-constrained, with unconstrained demand far higher. The call was dominated by massive multi-hundred-billion-dollar infrastructure buildouts and financial engineering (financing platforms, take-or-pay deals) aimed at funding 'compute-limited' AI labs. FY27 Q2 revenue was $96B ( YoY +100%), slightly above guidance, but Q3 guide of $108B came in just in line.
Guidance · revenue to $108B
FY27 Q2 revenue was $96B ( YoY +100%), slightly above guidance, but Q3 guide of $108B came in just in line.
Management guides to supply-constrained growth of ~70% in fiscal 2028, with capacity being a bottleneck. Hyperscaler capex is expected to reach ~$800B in 2026 and $1.3T in 2027, and NVIDIA is investing heavily in AI infrastructure, including partnerships to raise over $500B for…
Demand is accelerating, with customers' forecasts pointing to doubling growth next year, but NVIDIA is supply-constrained. Cloud industry backlog exceeds $2 trillion, and hyperscale customers are seeing strong financial results, while neocloud capacity is expanding rapidly to…
Management highlights that AI demand is surging across closed and open models, with NVIDIA's platform running every leading model and enabling agentic AI, which drives higher compute usage. They note AI is generating profitable tokens and customers are limited by compute, reinforcing NVIDIA's central role in AI monetization and adoption.
Demand is accelerating, with customers' forecasts pointing to doubling growth next year, but NVIDIA is supply-constrained. Cloud industry backlog exceeds $2 trillion, and hyperscale customers are seeing strong financial results, while neocloud capacity is expanding rapidly to meet enterprise and sovereign demand.
Management guides to supply-constrained growth of ~70% in fiscal 2028, with capacity being a bottleneck. Hyperscaler capex is expected to reach ~$800B in 2026 and $1.3T in 2027, and NVIDIA is investing heavily in AI infrastructure, including partnerships to raise over $500B for Frontier AI Labs and securing land/power for AI factories.
Management is confident and enthusiastic about demand, highlighting record growth, accelerating adoption, and strong customer economics, despite acknowledging supply constraints and margin pressures.
Higher memory costs are directly reducing NVIDIA's gross margins, guiding to the low 70s range.
“we are experiencing extreme pricing conditions in memory. The magnitude of the price increase has exceeded our prior expectations and are headed even higher into next year.”
Infrastructure availability limits the pace of AI factory deployment and NVIDIA's ability to meet soaring demand.
“you've got to go secure the land power and shell, which oftentimes is a couple, two, three years out.”
Supply constraints cap NVIDIA's revenue growth at 70% despite demand indicating 100% growth.
“we expect supply to remain a bottleneck at least through the end of fiscal year 28.”
“Since Hopper, our revenue opportunity has grown from roughly $18 billion per gigawatt to $25 billion with Blackwell to $40 billion with Vera Rubin”
“NVIDIA provides a take or pay commitment on a portion of the facility's capacity... and in exchange, we share in a portion of the Neocloud's revenue earned above that floor.”
“we recently announced partnerships with six of the world's leading infrastructure capital providers, Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR, to establish financing platforms that will raise over $500 billion of t…”
“there is no China data center compute revenue in our forward outlook.”
| Показатель | Период | Диапазон | Середина | Статус |
|---|---|---|---|---|
| Gross margin | FY2027 Q3 | 73.5%–74.5% | 74% | GUIDED |
| Gross margin | FY2027 Q4 | 71%–72% | 71.5% | GUIDED |
| Gross margin | FY2028 | 72%–73% | 72.5% | GUIDED |
| Revenue | FY2027 Q3 | $105.84B–$110.16B | $108B | GUIDED |
| Revenue | FY2028 | 70% | 70% | GUIDED |
| UnitsCPU | FY2028 | 100% | 100% | GUIDED |
| Дата прогноза | Показатель | Целевой период | Прогноз | Факт | Результат |
|---|---|---|---|---|---|
| FY2027 Q1 | Gross margin | FY2027 Q2 | 74.5%–75.5% | 75% | Met / beat |
| FY2027 Q1 | Revenue | FY2027 Q2 | $89.18B–$92.82B | $96B | Met / beat |
| FY2026 Q3 | Gross margin | FY2026 Q4 | 74.5%–75.5% | 75% | Met / beat |
| FY2026 Q3 | Revenue | FY2026 Q4 | $63.7B–$66.3B | $68.127B | Met / beat |
The BMS investment, following Roche and Lilly, signals accelerating AI adoption in pharma and life sciences, a new growth vector for NVIDIA's platform.
… growth. In enterprise, on a trailing 12-month basis, on-prem revenue in the automotive vertical reached $8 billion, while financial services, manufacturing, and healthcare combined contributed $7 billion in revenue. Hudson River Trading and Jane Street are leveraging NVIDIA's powered AI factories to accelerate quantitative trading. Samsung Electronics is using NVIDIA Kulitho to achieve up to 20X greater performance in computational lithography, while Bristol-Myers Squibb is investing in Vera Rubin AI Factory, a fast follow to the Roche and Lilly build-outs, as drug R&D timelines compress from years to months. In Sovereign AI, our business primarily through the regional neoclouds grew 35% sequentially and more than tripled year over year in Q2. A country or region can allocate land and power directly to a regional cloud partner in ways it never would to a foreign hyperscaler. We don't own a cloud ourselves. We are a neutral partner to every sovereign and neocloud. and because NVIDIA Compute is productive, fungible, rentable and durable, regional cloud interest is surging around the world. We helped Quarweave, Nebius and Nscale build entire infrastructure businesses and …
Nebius is the lead adopter of NVIDIA's new Grok 3 LPU rack-scale system, positioning it as an early customer of a key new product line that expands NVIDIA's TAM.
… leading server CPU suppliers. Since the announcement of our Grok partnership last year, we've been working to unite NVIDIA's high throughput and Grok's high interactivity architectures. At Hot Chips earlier this week, we announced that Grok 3 LPX, our first rack scale LPU system, is in full production and already setting records. demonstrating nearly 4x the number of tokens per second against the next best alternative on our artificial analysis benchmark. We expect to ship Grok 3 LPX in volume later this quarter to early adopters. Nebius will be the first. Today, we're not just selling the best chips. We're selling a full-stack AI factory platform, offering superior economics for customers and capturing a bigger share of the data center TAM. Our third unique capability is the combination of our full-stack AI factory and rich CUDA ecosystem, allowing us to extend AI into markets a single chip alone can never reach. Beyond the hyperscalers lies a massive market, anxious to adopt AI, customers with no interest in designing their own custom silicon. NVIDIA's fully proven full stack platform is uniquely suited to help sovereigns, neoclouds, and enterprises build their AI …
Oracle (OCI) is a lead partner deploying NVIDIA's new Vera CPU, confirming its data center buildout is heavily reliant on NVIDIA's next-gen platform.
Samsung adoption of NVIDIA's 'Kulitho' software showcases NVIDIA's expanding footprint into enterprise manufacturing applications, not just core data center AI.
… run rate revenue, up from 13 companies in Q4 of last year, with vertical enterprise software logging the fastest growth. In enterprise, on a trailing 12-month basis, on-prem revenue in the automotive vertical reached $8 billion, while financial services, manufacturing, and healthcare combined contributed $7 billion in revenue. Hudson River Trading and Jane Street are leveraging NVIDIA's powered AI factories to accelerate quantitative trading. Samsung Electronics is using NVIDIA Kulitho to achieve up to 20X greater performance in computational lithography, while Bristol-Myers Squibb is investing in Vera Rubin AI Factory, a fast follow to the Roche and Lilly build-outs, as drug R&D timelines compress from years to months. In Sovereign AI, our business primarily through the regional neoclouds grew 35% sequentially and more than tripled year over year in Q2. A country or region can allocate land and power directly to a regional cloud partner in ways it never would to a foreign hyperscaler. We don't own a cloud ourselves. We are a neutral partner to every sovereign and neocloud. and because NVIDIA Compute is productive, fungible, rentable and durable, regional cloud interest …
NVIDIA is helping Frontier AI Labs finance compute by partnering with capital providers to raise over $500B, effectively transferring infrastructure buildout risk to institutional capital while solidifying its own GPU pipeline. — This is a massive catalyst for AI infrastructure spending, ensuring that 'compute-limited' startups can access capital to buy NVIDIA hardware, sustaining demand for years.
… Each generation of NVIDIA AI factory systems deployed at Portspike could represent approximately 1.5 million NVIDIA GPUs. In over 20 years, the site could support multiple upgrade cycles. Here's the essential economic point. The LPS commitment secures a long-lived AI factory site while the NVIDIA compute within the data center can be upgraded repeatedly. This project deepens our longstanding partnership with OpenAI. OpenAI has committed to substantially deployments of NVIDIA AI infrastructure through 2030. OpenAI's existing and planned commitments represent approximately 12 gigawatts of NVIDIA compute. For another frontier AI lab, we will provide selective credit enhancement for nearly two gigawatts of compute. This complements the substantial NVIDIA compute capacity they've secured independently without NVIDIA's credit support. We recognize the scale of this support, and we know some will call this circular financing. We see it differently. We're going through a major computing platform shift. Thank you for joining us. We believe these investments, measured against the strength of their demand, the business they create for us, the ecosystem they build on NVIDIA's platform, …
AWS is expanding its NVIDIA deployment by 2 million GPUs, cementing NVIDIA's position as a key supplier and driving multi-year revenue visibility.
… drives more revenue as new GPU capacity comes online, our hyperscale customers delivered strong financial results in the quarter with accelerating revenue growth and expanding margins. With cloud industry backlog now greater than 2 trillion, CapEx by the top five hyperscalers is expected to reach nearly 800 billion in 2026 and 1.3 trillion in 2027. Today we are delighted to announce an expansion of our partnership with AWS. Building on its already vast installed base of NVIDIA compute, AWS is deploying an additional 2 million GPUs starting this quarter through the second quarter of fiscal 29. Along with Vera CPUs, some integrated with Ruben, others standalone. AWS will serve NVIDIA Nematron family of open models on Amazon Bedrock and SageMaker. Amazon will also adopt our full physical AI stack, Omniverse, Cosmos, Isaac, and Jetson to power its fleet of warehouse robots. ACI and E revenue of 40 billion increased 25% sequentially and 138% year over year. Growth was driven by neocloud capacity additions to meet the rising demand from enterprises, AI startups, and sovereigns, as well as hyperscalers purchasing capacity to supplement their own build-outs. Using NVIDIA DSX reference …
The SoftBank partnership secures 4.25GW of capacity for OpenAI, demonstrating NVIDIA's ability to orchestrate large-scale infrastructure deals that benefit its ecosystem.
… infrastructure capital providers, Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR, to establish financing platforms that will raise over $500 billion of third-party capital. With these partnerships, building on our unique, fungible, and durable computing platform, the AI labs will be able to build and assess AI infrastructure funded by long-term institutional capital at relatively attractive rates. Last week, we announced that we secured land power shell capacity through our partnership with SoftBank Energy to exclusively host NVIDIA Compute at their Portsmouth campus. The initial deployment expected to support 4.25 gigawatts of AI factory capacity will be utilized by OpenAI. Each generation of NVIDIA AI factory systems deployed at Portspike could represent approximately 1.5 million NVIDIA GPUs. In over 20 years, the site could support multiple upgrade cycles. Here's the essential economic point. The LPS commitment secures a long-lived AI factory site while the NVIDIA compute within the data center can be upgraded repeatedly. This project deepens our longstanding partnership with OpenAI. OpenAI has committed to substantially deployments of NVIDIA AI …
LG is partnering with NVIDIA to build AI capabilities, highlighting NVIDIA's expansion into traditional industrial sectors.
… are emerging everywhere. Firebird in Armenia, Casaba Technologies across Africa, GMI Cloud in Taiwan, Yoda and Naysa in India, Hermes in Australia, YTL-AI Cloud in Malaysia, pairing local land, power and operating expertise with our platform. Last month, we announced a partnership with NOATRA, Japan's national AI company, to build an NVIDIA DSX AI factory that will create open models to power AI agents, digital twins, robotics, and physical AI applications. South Korea's LG and Hyundai Motor Group are partnering with NVIDIA to build and scale AI. and in Europe, a record 35 new NVIDIA powered AI supercomputers were unveiled to advance industry and scientific breakthroughs. Neoclouds are seeing strong demand pipelines for many diverse off-takers. Rather than allocating their entire capacity to a single long-term off-take guarantee that lenders typically require to finance a data center independently, we have introduced a revenue sharing structure. NVIDIA provides a take or pay commitment on a portion of the facility's capacity, a minimum revenue guarantee that gives lenders the confidence to underwrite the project, and in exchange, we share in a portion of the Neocloud's revenue …
Memory price increases are so extreme they will cause NVIDIA's gross margins to bottom at 71-72% in Q4 before recovering, signaling a major inflection in memory pricing power. — Memory suppliers have unprecedented pricing power, directly squeezing NVIDIA's margins, a significant reversal from prior quarters.
… about 20% of data center revenue in Q3. Looking ahead, our preliminary expectation is for fiscal year 28 revenue to grow approximately 70% year over year. Although we will work to close the supply demand gap, we expect supply to remain a bottleneck at least through the end of fiscal year 28. Many of you have expressed concerns regarding our gross margins as component costs have risen significantly. As you are already aware, we are experiencing extreme pricing conditions in memory. The magnitude of the price increase has exceeded our prior expectations and are headed even higher into next year. As a result, we are resetting expectations today. For Q3, we expect gap and non-gap gross margins to be 74%, plus or minus 50 basis points. We expect margins to bottom in Q4 in the 71% to 72% range. before settling at 72% to 73% in fiscal year 28 as executed price increases take effect in Q1. We want to be direct about this rather than let it linger as an open question. Memory scarcity today is being driven in large part by the AI build-out itself and unlike a component that simply raises our costs with no offset benefit. Tighter memory supply is a symptom of the same demand surge that's …
NVIDIA confirms that in Q2 it shipped 'less than 1%' of data center revenue in Hopper products to China and is excluding China from future revenue outlook due to geopolitical uncertainty. — The near-total exclusion of China from NVIDIA's growth plans means hyperscalers and sovereigns outside China are disproportionately driving demand.
… leverage our balance sheet to contribute toward roughly a quarter of our business next year. This remains compute we ship will be consumed by investment grade customers or those that are backed by one. In Q2, we ship less than 1% of our total data center revenue in Hopper 200 products to customers based in China in accordance with the U.S. government licenses. Current Hopper shipments are dilutive to corporate gross margins. And given ongoing geopolitical uncertainty, there is no China data center compute revenue in our forward outlook. Moving to the rest of the P&L, GAAP and non-GAAP gross margins were both 75%, largely unchanged from last quarter due to a similar product mix. GAAP and non-GAAP operating expenses were up 10% and 11% sequentially, primarily due to high compute infrastructure costs and compensation and benefits costs. Our non-GAAP effective tax rate of 16% increased from a year ago, primarily due to higher revenue. On our balance sheet, inventory increased to 32 billion as we prepared for the Vera Rubin launch. Days of sales outstanding increased to 60 days reflecting extended payment terms for large purchases by certain investment grade customers to be shipped …
NVIDIA is helping Frontier AI Labs finance compute by partnering with capital providers to raise over $500B, effectively transferring infrastructure buildout risk to institutional capital while solidifying its own GPU pipeline. — This is a massive catalyst for AI infrastructure spending, ensuring that 'compute-limited' startups can access capital to buy NVIDIA hardware, sustaining demand for years.
… For these companies, more compute means more and more intelligence, more users, and more revenue. NVIDIA is needed to help power this flywheel. First, we've invested nearly 50 billion in the Frontier AI Labs. This was a meaningful commitment, but it represented a small fraction of our expected free cash flow over the same period. Further, to support the Frontier Labs infrastructure build-outs, we recently announced partnerships with six of the world's leading infrastructure capital providers, Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR, to establish financing platforms that will raise over $500 billion of third-party capital. With these partnerships, building on our unique, fungible, and durable computing platform, the AI labs will be able to build and assess AI infrastructure funded by long-term institutional capital at relatively attractive rates. Last week, we announced that we secured land power shell capacity through our partnership with SoftBank Energy to exclusively host NVIDIA Compute at their Portsmouth campus. The initial deployment expected to support 4.25 gigawatts of AI factory capacity will be utilized by OpenAI. Each generation of NVIDIA …
NVIDIA's revenue per gigawatt of data center capacity has more than doubled from $18B (Hopper) to $40B (Vera Rubin) and is expected to keep rising, meaning each new generation dramatically increases NVIDIA's TAM per unit of power.
… in the edge. NVIDIA is great at training, great at inference, great at agentic workloads. One platform, fungible for every model and workload, durable for the entire lifecycle of AI. That combination of performance, fungibility, and durability is what makes NVIDIA the productive and financeable compute infrastructure. Our second unique capability is our full-stack AI factory platform that is expanding our share of the data center TAM. Since Hopper, our revenue opportunity has grown from roughly $18 billion per gigawatt to $25 billion with Blackwell to $40 billion with Vera Rubin, which now spans Vera CPU, Rubin GPU, NVLink, InfiniBanner Ethernet, and Grok LPU announced earlier this week. Our ability to extreme code design across GPU, CPU, NB-Link scale-up networking, scale-out networking systems, algorithms, and software enables us to deliver X-factor performance gain every generation. Vera Rubin exemplifies this, delivering 30X higher throughput per megawatt and 35X lower token costs relative to Grace Blackwell Ultra. We commenced production shipments of Vera Rubin earlier this month. Having already received purchase orders from every major hyperscaler, AI cloud, and system …
NVIDIA is implementing 'take-or-pay' revenue sharing deals with neoclouds, providing minimum revenue guarantees to get financing while sharing upside, a new model that could generate billions in recurring revenue.