Cycle on Jun 30, 2026

I will start by listing the active threads and reading the existing notes for the topic to see what prior research has established and check for any open questions or registered watches.

I will read the existing notes for the topic to see what findings are already recorded and their slugs.

The brief asks: "Is Nvidia's AI capex story still intact?" Let's look at the prior findings: 1. `big-tech-capex-reaches-710b-in-2026` (Big Tech's AI Capex Reaches Historic Scale as Hyperscalers Guide Up to $725B in 2026) 2. `nvidia-record-q1-results-and-trillion-dollar-order-book` (Nvidia's AI Capex Story Remains Intact Amid Blockbuster Q1 Results and Vera Rubin Production Ramp) 3. `gpu-specialized-clouds-and-strategic-co-investment` (Specialized GPU Clouds Gain Index Inclusion and Scale Backlogs Amid Heavy Debt and Widening Losses) 4. `custom-silicon-and-datacenter-hardware-competition` (Custom Silicon and Data Center Hardware Competition Escalates to Challenge Nvidia's Moat) 5. `ai-monetization-proofs-and-infrastructure-bottlenecks` (Local and Federal Lawmakers Enact Data Center Moratoriums as Environmental and Power Bottlenecks Intensify) Let's use `market_view` to get the latest public markets view for `NVDA`, as well as macro and relevant sectors or competitors. Let's start with `NVDA` and other key players if possible (e.g. MSFT, GOOGL, AMZN, META, ORCL, etc. or sector/macro). First, we must call `market_view` with kind='ticker' and id='NVDA'. Let's do that.

The market view for NVDA shows: - Revenue (TTM): $253.49B (+85.2% YoY) - Gross margin: 74.1% - Net income for latest quarter (ending 2026-04-30): $58.32B on $81.61B revenue (very high profit margin). - Stock is currently priced at $194.97 with a market cap of $4.72T (down 7.6% over the past month, and 17.2% below its 52-week high). - Let's check the macro environment and key customers' market views to see how their capex profiles are shaping up. Let's do `market_view` for macro first.

Okay, now let's perform some web searches to see if there is any new information or developments regarding Nvidia's AI capex story, hyperscaler capex, or AI hardware demand. Let's search for "Nvidia AI capex story", "Nvidia Blackwell demand", "hyperscaler capex Q2 2026", and "Nvidia AI capex intact". We want to understand what's happening right now in late June 2026. Let's do a search.

Let's search for some of the URLs or search more specifically. Let's see what the CNBC article in late May 2026 says about: "AI spending expected to top $1 trillion in 2 years. Why that estimate may be too low." Let's fetch that page. Or let's search specifically for the CNBC page. Let's fetch: `https://www.cnbc.com/2026/05/21/ai-spending-expected-to-top-1-trillion-in-2-years-why-that-estimate-may-be-too-low.html` Let's call `web_fetch` for that URL.

This CNBC article is from May 21, 2026, following Nvidia's Q1 FY2027 earnings call (which occurred on Wednesday evening, May 20, 2026). Let's analyze the quotes: Jensen Huang said: "The capex is at a trillion dollars, and it’s growing toward the three to four [trillion-dollar mark]" speaking of hyperscalers. CFO Colette Kress: "With analysts now forecasting hyperscale capex to exceed $1 trillion in 2027 and agentic AI beginning to proliferate [across] all industries, AI infrastructure spending is on track to reach $3 to $4 trillion annually by the end of this decade." This is a massive expansion from previous estimates. Let's see if there are any updates in June 2026 about Nvidia's AI capex story, Blackwell shipments, or any challenges. Let's do a web search. Let's search for "Nvidia Blackwell delay" or "Nvidia Blackwell architecture shipment" or "Nvidia capex June 2026". Let's search for: `Nvidia Blackwell shipments 2026` or `Nvidia Blackwell demand H2 2026`.

Ah, let's look at the "TrendForce" report about "Rubin Faces Delays; Blackwell to Drive 70%+ of NVIDIA High-End GPU Shipments in 2026". Let's search for "TrendForce Nvidia Rubin delay 2026" to find the detailed report. Let's do that.

Let's fetch `https://www.trendforce.com/presscenter/news/20260408-13003.html` to see what TrendForce says. Wait, the URL is `/20260408-13003.html` which is April 8, 2026. Let's inspect this report. This is very relevant to the Rubin timeline and Blackwell dominance in 2026. Let's call `web_fetch` on it.

This is extremely interesting! Let's see: - TrendForce notes that the Rubin series is facing shipment delays (due to HBM4 validation, transitioning network interconnects from CX8 to CX9, high power consumption, and advanced liquid cooling optimizations). - As a result, Rubin's share of Nvidia's high-end GPU shipments in 2026 is revised down from 29% to 22%. - The Blackwell series is projected to grow from 61% to 71% of high-end shipments, solidifying its leading position in 2026. - The Hopper series is forecast to drop from 10% to 7%. - Total high-end GPU shipments will still grow, with the annual growth rate slightly revised downward from 26.8% to around 26%. - Nvidia is expanding into AI inference applications, specifically mentioning: "Demand for its new LPU solutions is expected to reach several hundred thousand units in 2026, with a target to double in 2027." This is likely related to the Groq acqui-hire or other LPUs (Language Processing Units). - Wait, let's search for "Nvidia LPU" or "Nvidia Groq" or "Nvidia Q1 FY2027 earnings transcript" to see what Nvidia says about LPUs, Blackwell, and Rubin. Let's search for: `Nvidia Q1 FY2027 earnings call transcript` or `Nvidia Q1 2027 earnings call transcript`. Let's search.

Let's fetch the Motley Fool transcript: `https://www.fool.com/earnings/call-transcripts/2026/05/20/nvidia-nvda-q1-2027-earnings-transcript/` to get the actual quotes and details. This is extremely valuable! Let's do a `web_fetch` on it.

Wow, this is an incredible, highly detailed transcript! Let's examine the key numbers in this Q1 FY2027 report (which ended around April 30, 2026, and was reported on May 20, 2026): - Total Revenue: $82 billion (actually $81.61 billion from the `market_view` data, rounded to $82 billion in the transcript summary), up 85% year over year and 20% sequentially. - Data Center Revenue: $75 billion, up 92% year over year and 21% sequentially. - Data Center Computing Revenue: $60 billion, up 77% YoY. - Data Center Networking Revenue: $15 billion, nearly tripled YoY. - Segmented into: - Hyperscale Subsegment: $38 billion (~50% of data center revenue), up 12% sequentially. - ACIE (AI Cloud, Industrial, and Enterprise) Subsegment: $37 billion, up 31% sequentially, with AI cloud revenue more than tripling YoY. - Partner Data Centers over 10MW: number nearly doubled in 1 year, now above 80 sites. - Sovereign Revenue: Grew more than 80% YoY, deployed in nearly 40 countries. - AI Infrastructure Pricing: H100 rental prices increased 20% year to date; A100 cloud pricing up nearly 15%. This shows extreme pricing power and utilization. - InfiniBand Revenue: More than quadrupled YoY, bolstered by next-generation XDR deployments. - Grace Blackwell Throughput: Blackwell Ultra delivered 2.7x throughput boost and 60% reduction in cost-per-token on GV300 over the last 6 months. - Vera CPU Platform: Anticipated $20 billion in standalone CPU revenue for the year, opening a $200 billion market opportunity. - Production shipments of VeraRubin: Set to begin in Q3, with ramp continuing into following quarters. Wait! TrendForce noted some shipment delay risks for Rubin, but the official timeline from Nvidia is that production shipments of VeraRubin are set to begin in Q3 (which likely refers to Q3 FY2027, i.e., Aug-Oct 2026, or Q3 calendar year 2026). - Supply Commitments: Total supply, including inventory purchase commitments and prepaids, increased to $145 billion. - GAAP Gross Margin: 74.9% (non-GAAP 75%), flat sequentially as Blackwell accounted for most shipments. - Q2 Revenue Outlook: Expected $91 billion (+/- 2%). - China Data Center Revenue: No China compute revenue included in outlook, as no H200 shipments have yet occurred or are anticipated under current circumstances. - Buyback: Announced $80 billion new buyback program, in addition to $39 billion left on current plan. - Dividend: raised from $0.01 to $0.25 per share. Let's check if there are any specific comments about "agentic AI", "parabolic demand", etc. Let's search the transcript for specific quotes or read more about the Q1 earnings. Let's look at the actual text of the transcript to get some verbatim quotes of Jensen Huang and Colette Kress. We can search for the term `parabolic` or `agentic` in the transcript, or look for the exact Q&A. Wait, let's search Google for the exact text of the transcript or do a web search for specific sections of the transcript to get verbatim quotes. Let's do a search for: `site:fool.com "nvidia" "q1 2027" "transcript" "agentic"` or similar. Or we can search for quotes from Jensen Huang on the Q1 FY2027 call. Let's do that.

Let's fetch `https://s201.q4cdn.com/141608511/files/doc_financials/2027/q1/NVDA-Q1-2027-Earnings-Call-20-May-2026-5_00-PM-ET.pdf` or search for terms within it. Wait, can we fetch a PDF using `web_fetch`? Let's check. Yes, sometimes PDFs are parsed as text or markdown, but let's see if we can search for specific quotes first. Let's search for: `site:barrons.com "demand has gone parabolic" "agentic AI"` to get the exact quote from Barrons. Let's call `web_fetch` on `https://www.barrons.com/livecoverage/nvidia-earnings-stock-price-ai-chips-jensen-huang/card/jensen-huang-closes-out-call-demand-has-gone-parabolic--EhNBWTnEve78UZ9arO6M` or fetch standard text from SiliconANGLE or wisemanc.substack.com. Let's do `web_search` to see if we have other good articles. Wait, let's fetch: `https://wisemanc.substack.com/p/demand-has-gone-parabolic-nvidia` or `https://siliconangle.com/2026/05/21/five-takeaways-nvidias-earnings-mean-ai-industry/`. Let's do a search to see the SiliconANGLE URL. Yes, it's listed above. Let's call `web_fetch` on it.

This is an outstanding source. Let's look at the key details: - **Total Revenue**: $81.61B (reported as $82B), up 85% YoY and 20% sequentially. - **Data Center Revenue**: $75 billion (out of $81.61B total, meaning data center is ~92% of Nvidia's total business now!). - **Hyperscale Subsegment**: $38 billion (~50% of data center), up 12% sequentially. - **ACIE (AI Clouds, Industrial, and Enterprise) Subsegment**: $37 billion, up 31% sequentially, with AI cloud revenue more than tripling YoY. - **Pricing Power / Utilization**: H100 rental prices increased 20% year to date; A100 cloud pricing up nearly 15%. This is a huge indicator that GPU demand remains extremely high and supply is tight, allowing pricing to actually increase even for older-generation GPUs. - **Vera CPU Platform**: Anticipates $20 billion in standalone CPU revenue for the year, opening a $200 billion market opportunity. - **VeraRubin Production Shipments**: Set to begin in Q3, with ramp continuing into following quarters. (Note that calendar Q3 2026 starts in July/August, which matches Nvidia's Q3 FY2027 starting August). - **Supply Commitments**: Total supply, including inventory purchase commitments and prepaids, increased to $145 billion. - **GAAP Gross Margin**: 74.9% (Non-GAAP 75%), flat sequentially. - **Free Cash Flow**: Generated $49 billion in Q1 FY2027, up from $35 billion in the prior quarter. This is a staggering cash machine. - **Capital Allocation**: Raised dividend from $0.01 to $0.25 per share. Announced a massive new $80 billion buyback program (on top of $39 billion remaining, for a total of $119 billion in buyback capacity). - **Q2 Revenue Outlook**: Guided to $91 billion (+/- 2%), led by data center. Let's check the other companies' recent earnings or news to see if there are any signs of AI capex slowing down or changes in plans. Wait, let's look at the existing watches: - `019f10c8-53dd-729c-926a-27e735d10910`: Alphabet Q2 2026 Earnings (expected late July 2026). - `019f0ba3-59a5-7471-b2e6-7c9feacff247`: Alphabet $40B ATM Stock Offering Execution. - `019ef70b-6b49-7831-893f-6d78e9b2099e`: Oracle $40B Debt and Equity Financing Plan for FY2027. - `019ef1e2-810a-7234-ab4a-1680b5c05e86`: NY Governor Hochul action on Data Center Moratorium Bill (expected by July 15, 2026). - `019ee796-b599-775e-b0db-e799779d71a4`: Anthropic public S-1 filing and IPO debut (expected Nov 15, 2026). - `019edd49-1ccb-73d3-9fc0-80ae266f32c4`: Nebius Group Q2 2026 earnings (expected Aug 15, 2026). - `019ed2f6-f136-7051-a5b0-fa3b26ec02e0`: Nvidia Q2 FY2027 Earnings Release (expected late August 2026). - `019eb93f-9403-7dea-9c9e-9ac0765dd674`: Meta Platforms potential equity raise. - `019eaeeb-7009-7e9b-9b2f-d6c2f4ec5339`: Nebius 850 MW active power capacity by YE 2026. - `019eaeeb-61e2-71a6-b308-0186f59be87f`: CoreWeave quarterly capex tracking. - `019e9f7b-8898-71ef-a8fc-916318c1f6ed`: Vera Rubin platform broader commercial shipments in H2 2026. Wait, are there any watches that have fired or can be resolved? Let's see: - "NY Governor Hochul action on Data Center Moratorium Bill" (fire_date: July 15, 2026). Today is June 30, 2026. This hasn't happened yet. - "Alphabet Q2 2026 Earnings" (fire_date: July 25, 2026). Hasn't happened yet. - "Nebius Group Q2 2026 earnings" (fire_date: Aug 15, 2026). Hasn't happened yet. - "Nvidia Q2 FY2027 Earnings" (fire_date: Aug 20, 2026). Hasn't happened yet. - Let's search the web for "Responsible Data Center Development Act" or "A11560" or "S10642" or "Governor Hochul" to see if there is any update on whether the New York data center moratorium has been signed or vetoed. Let's do that! This could resolve a thread.

The bill was passed on June 4, 2026, and is awaiting the governor's signature or veto. It seems it has not yet been signed or vetoed as of June 30, 2026, so that watch has not fired yet. Let's keep it open. Wait, let's look at the other watches: "Long-Term Impact of Custom Silicon on Nvidia's Pricing Power and Margins" is a question thread (id: `019f0679-f319-75c7-b35d-6dea5ba6b6d4`). Let's see if we can address it or find any new information about custom silicon or alternative hardware. Let's search for "OpenAI Jalapeño chip" or "Qualcomm Dragonfly C1000" or other custom silicon. Let's do a search.

This is incredibly fresh and highly relevant! "OpenAI and Broadcom's AI chip has a name: Jalapeño" was unveiled on June 24 or 25, 2026. Let's fetch the Tom's Hardware article: `https://www.tomshardware.com/tech-industry/artificial-intelligence/broadcom-and-openai-unveil-custom-built-jalapeno-inference-processor-openais-first-chip-is-a-massive-reticle-sized-asic-built-in-an-ultra-fast-nine-month-development-cycle` to read all about it. This directly relates to custom silicon competition and the long-term impact on Nvidia's pricing power and margins. Let's do that.

Ah, the Tom's Hardware article is behind a paywall or has a weird structure where it just shows the subscription plans. Let's try to fetch another source for OpenAI's Jalapeño. Let's try: `https://www.techzine.eu/news/infrastructure/142460/openai-and-broadcom-unveil-jalapeno-ai-inference-chip/` or `https://news.ycombinator.com/item?id=48663324` or another web search. Let's search for "OpenAI Broadcom Jalapeno chip details" to see other candidate URLs. Let's do that first.

This is extremely useful. Let's fetch the official announcement from OpenAI if possible, or Broadcom's press release, or CNBC. Let's see: `https://openai.com/index/openai-broadcom-jalapeno-inference-chip/` (OpenAI official announcement) and `https://investors.broadcom.com/news-releases/news-release-details/openai-and-broadcom-unveil-llm-optimized-intelligence-processor` (Broadcom official announcement) and `https://www.cnbc.com/2026/06/24/openai-and-broadcom-reveal-jalapeno-first-ai-chip-in-partnership.html` (CNBC article). Let's call `web_fetch` on `https://investors.broadcom.com/news-releases/news-release-details/openai-and-broadcom-unveil-llm-optimized-intelligence-processor` or the OpenAI one. Let's try the Broadcom press release first. It might be very detailed and free of paywalls.

This is an exceptionally rich, primary source document! Let's examine the details of the OpenAI and Broadcom "Jalapeño" announcement on June 24, 2026: - OpenAI and Broadcom unveiled **Jalapeño**, OpenAI's first custom AI chip, which they call an "Intelligence Processor." - It is an accelerator designed from the ground up for LLM inference (not training). - It was co-developed from initial design to manufacturing tape-out in just **nine months**, which is exceptionally fast and was accelerated by OpenAI's own AI models. - Early testing indicates performance per watt is "substantially better than current state-of-the-art." - It will be deployed at **gigawatt scale** with data center partners (like Microsoft) beginning in **2026** (over multiple generations). - Partners include Broadcom (for silicon implementation and networking/Tomahawk silicon) and Celestica (for board, rack, and system integration). - The chip is already running ML workloads in the lab at production target frequency and power, including "GPT-5.3-Codex-Spark." This is a very interesting naming detail (suggesting GPT-5.3 or Codex-Spark is a key upcoming model). Let's look at the implications for Nvidia. The brief asks: "Is Nvidia's AI capex story still intact?" Yes, in the near-to-mid term, Nvidia's capex story is extremely intact because: 1. Demand is "parabolic" according to CEO Jensen Huang, driven by the emergence of "agentic AI." 2. In Q1 FY2027 (ended April 30, 2026), Nvidia generated record-shattering $81.61B in revenue (up 85% YoY and 20% sequentially), with Data Center revenue at $75 billion (up 92% YoY and 21% sequentially). 3. Nvidia's gross margin remains extremely high at 74.9% (GAAP) / 75.0% (Non-GAAP), demonstrating massive pricing power. 4. AI infrastructure pricing actually increased (H100 rental prices up 20% YTD, A100 cloud pricing up nearly 15%). This is direct evidence that demand continues to outstrip supply, even for older chips. 5. In addition to GPUs, Nvidia is opening a new $200 billion total addressable market (TAM) with its custom **Vera CPU**, which is purpose-built for agentic AI workloads (where the CPU handles the orchestration harness/tools and the GPU handles inference/thinking). Standalone CPU revenue is expected to reach $20 billion in FY2027. 6. Hyperscaler capex is projected to exceed $1 trillion in 2027, and Nvidia/analysts forecast AI infrastructure spending to reach $3 to $4 trillion annually by the end of the decade. 7. Nvidia's supply commitments (inventory purchase commitments and prepaids) increased to a massive $145 billion. However, long-term competitive dynamics are starting to shape up: 1. Custom ASICs are emerging at scale. OpenAI's "Jalapeño" chip (co-developed with Broadcom and Celestica) is a major milestone. It is a blank-slate design optimized specifically for LLM inference, tape-out in 9 months, and set to be deployed at gigawatt scale starting in late 2026. This represents a direct threat to Nvidia's inference dominance, which is where much of the volume is expected to shift as models transition from training to production. 2. In addition, TrendForce reports that the next-generation Vera Rubin platform faces some delay risks in its volume ramp (due to HBM4 validation, CX8 to CX9 network interconnect transitions, high power consumption, and liquid cooling optimizations). Because of this, TrendForce revised Rubin's share of Nvidia's high-end GPU shipments in 2026 down from 29% to 22%, with the more mature Blackwell platform projected to dominate at over 70% of shipments. Let's check if there are other companies or tickers with relevant data. Wait, let's search for "Qualcomm Dragonfly C1000" or other custom silicon updates. Let's do a search.

This is also incredibly fresh! This happened in June 2026 as well (specifically around Qualcomm's data center solutions announcement, which is deployed by Meta!). Let's fetch: `https://www.qualcomm.com/news/releases/2026/06/qualcomm-unveils-comprehensive-data-center-roadmap-for-the-agent` or the datacenterdynamics article to read all about it. Let's do a `web_fetch` on `https://www.datacenterdynamics.com/en/news/qualcomm-unveils-three-new-data-center-solutions-including-qualcomm-dragonfly-c1000-cpu-set-to-be-deployed-by-meta/`. Let's see if we can read it.

This is incredibly significant! Let's analyze this Qualcomm announcement from June 25, 2026: - Qualcomm has unveiled a new data center roadmap targeting "agentic AI" workloads. - Products include: 1. **Qualcomm Dragonfly C1000 CPU**: features custom Oryon cores, 250+ core-count, and is designed for agentic, general-purpose, and AI head node workloads. It claims a 2x better performance per watt compared to existing server CPU benchmarks. It will be commercially available in **2028**. 2. **Qualcomm Dragonfly AI300 inference accelerator**: 3rd-generation, air- and direct-liquid-cooled rack-level solution for disaggregated inference. Commercial sampling is expected in **2028**. 3. **Qualcomm High Bandwidth Compute (HBC)**: 3D-stacked silicon near-memory computing architecture to address memory bottlenecks. Commercial sampling of HBC Gen 1 with AI250 is expected in **mid-2027**, and AI300 with HBC Gen 2 in **2028**. - Major Win: Qualcomm signed a **multi-year partnership with Meta** for the deployment of the Dragonfly CPU. The C1000 will power Meta's next-generation server fleet. - This directly challenges Nvidia's new **Vera CPU** (which Nvidia estimates will bring $20B in standalone revenue in FY2027 and addresses a $200B TAM). Qualcomm's entry with the Dragonfly C1000, backed by Meta, represents a major long-term challenge to Nvidia's full-stack strategy (CPU + GPU). Wait, let's review the existing findings and see if we can update them or create new ones. Let's see: 1. `nvidia-record-q1-results-and-trillion-dollar-order-book` (Nvidia's AI Capex Story Remains Intact Amid Blockbuster Q1 Results and Vera Rubin Production Ramp) This is the perfect note to update with Nvidia's Q1 FY2027 results, the parabolic demand for agentic AI, the Vera CPU, the pricing power indicators (H100 and A100 pricing increases), and the TrendForce Rubin delay risks. Let's first read the existing note of `nvidia-record-q1-results-and-trillion-dollar-order-book` to make sure we preserve its key details while updating it. Wait, I can read the previous note body if I fetch it, but `read_notes` only returned previews. Let's do a quick search or see if we can read the note. Oh, is there a way to read the full note? No direct tool to read a specific note's full body, but we can search for it or just overwrite it with a comprehensive, updated version that preserves the core story and incorporates all the new Q1 FY2027 facts (which were reported on May 20, 2026, and the subsequent developments in June 2026). Let's write a very detailed and thorough note. Wait, let's look at the other note: `custom-silicon-and-datacenter-hardware-competition` (Custom Silicon and Data Center Hardware Competition Escalates to Challenge Nvidia's Moat) This is the perfect note to update with: - **OpenAI and Broadcom's "Jalapeño" chip**: Unveiled on June 24, 2026. A custom inference "Intelligence Processor" built in just 9 months, optimized for LLMs, to be deployed at gigawatt scale with Microsoft and other partners starting in late 2026. - **Qualcomm's "Dragonfly C1000" CPU, Dragonfly AI300, and High Bandwidth Compute (HBC)**: Unveiled on June 25, 2026, with a multi-year partnership with Meta to power its next-generation server fleet. This directly targets Nvidia's new Vera CPU and AI inference footprint, with commercial sampling starting in mid-2027 to 2028. Let's look at the other notes: - `big-tech-capex-reaches-710b-in-2026` (Big Tech's AI Capex Reaches Historic Scale as Hyperscalers Guide Up to $725B in 2026) Wait, this note has a lot of details about Big Tech capex. Let's check if there are any updates to Big Tech capex. Wait, let's look at the CNBC article on AI spending topping $1 trillion in 2 years. It states that Nvidia's CFO Colette Kress projected that "AI infrastructure spending is on track to reach $3 to $4 trillion annually by the end of this decade." And Jensen Huang said "The capex is at a trillion dollars, and it’s growing toward the three to four [trillion-dollar mark]" for hyperscalers. Let's see if there are other details. Let's write the first updated note on Nvidia's results and capex story under `nvidia-record-q1-results-and-trillion-dollar-order-book`. Wait, let's verify if there are other things to mention in `nvidia-record-q1-results-and-trillion-dollar-order-book`. Let's see: - Nvidia's Q1 FY2027 (ended April 30, 2026) results: - Total Revenue: $81.61 billion (guided to $91 billion for Q2 FY2027 +/- 2%). - Data Center Revenue: $75 billion (up 92% YoY and 21% sequentially), which is ~92% of total revenue. - GAAP Gross Margin: 74.9%, remaining flat sequentially. - Net Income: $58.32 billion. - Free Cash Flow: $49 billion (up from $35 billion in the prior quarter). - Capital returns: Raised dividend from $0.01 to $0.25, and announced a new $80 billion share buyback program. - Pricing Power: H100 rental prices increased 20% YTD, and A100 cloud pricing increased nearly 15%. This shows that despite Blackwell's ramp, older-generation GPU demand is so strong that pricing is actually rising, confirming that the capex story is extremely intact. - Vera CPU: Nvidia's new custom CPU purpose-built for agentic AI workloads is expected to generate $20 billion in standalone revenue in FY2027, opening a new $200 billion TAM. - Production shipments of VeraRubin are set to begin in Q3. - Undercurrents of supply chain risks: TrendForce (April 2026) reported that the Rubin platform faces delay risks (due to HBM4 validation delays, CX8 to CX9 interconnect transitions, high power consumption, and liquid cooling optimizations), which has led TrendForce to revise Rubin's share of Nvidia's high-end GPU shipments in 2026 down from 29% to 22%. Blackwell is projected to dominate at 71% of shipments. Let's write this note. Let's make sure we cite `/markets/NVDA/2026/06/30` for the financial figures and the SiliconANGLE and CNBC articles for the quotes. Let's do that! No YAML frontmatter. First heading is `# <Title>`. Let's draft it.

Now, let's update the second note: `custom-silicon-and-datacenter-hardware-competition` (Custom Silicon and Data Center Hardware Competition Escalates to Challenge Nvidia's Moat). Let's see what we can add here: - OpenAI and Broadcom's "Jalapeño" custom ASIC: Unveiled on June 24, 2026. This is OpenAI's first custom chip, an "Intelligence Processor" designed from scratch for LLM inference. It was co-developed and taped out in an ultra-fast nine months, accelerated by OpenAI's own models. It is running GPT-5.3-Codex-Spark in the lab and is set to deploy at gigawatt scale with Microsoft and other data center partners starting in late 2026. This represents a direct threat to Nvidia's inference dominance. - Qualcomm's "Dragonfly C1000" CPU and data center roadmap: Unveiled on June 25, 2026. This is Qualcomm's first-ever server CPU, featuring 250+ custom Oryon cores and claiming a 2x performance-per-watt advantage over existing server CPUs. Crucially, Qualcomm signed a multi-year partnership with Meta to deploy the Dragonfly C1000 across Meta's next-generation server fleet. This directly challenges Nvidia's new Vera CPU and agentic AI head node strategy. - Qualcomm also introduced the Dragonfly AI300 inference accelerator and High Bandwidth Compute (HBC) 3D-stacked silicon technology to bypass HBM bottlenecks, with commercial sampling expected between mid-2027 and 2028. Let's write this updated note. Let's make sure we cite the Broadcom press release, the Techzine article, and the DatacenterDynamics article for the Qualcomm and Meta details. Let's do that! No YAML frontmatter. First heading is `# <Title>`. Let's draft it.

This is excellent. Let's review the threads and watches. Are there any threads to resolve? Let's list the threads again to see their IDs and if we can resolve any: - `019f0679-f319-75c7-b35d-6dea5ba6b6d4`: Long-Term Impact of Custom Silicon on Nvidia's Pricing Power and Margins. This is a question thread. We have a lot of new evidence on this question (OpenAI's Jalapeño and Qualcomm's Dragonfly C1000). But is it fully resolved? It's a long-term question, so it might remain open, or we can resolve it with our current findings. Let's see if we should resolve it or keep it open. It's a "question" thread, so resolving it with a solid summary of what we found in this cycle is highly appropriate. Let's resolve it. - Let's check other threads. Is there a thread for "OpenAI Jalapeño chip initial production deployment" (id: `019f0679-7d60-7d01-98b1-601ff5664523`, fire_date: 2026-12-15)? This is a watch. It is forward-looking and has a fire date of late 2026. This hasn't happened yet, so we don't resolve it. Wait, let's see if there are other watches we should register. What about Qualcomm? Qualcomm announced the Dragonfly C1000 and AI300, but they are expected in 2028, and sampling of HBC Gen 1 is expected in mid-2027. We can register a watch for Qualcomm's data center CPU sampling or deployment. Let's see: "Qualcomm Dragonfly C1000 and HBC Gen 1 commercial sampling". Let's register a watch for this. And what about OpenAI's Jalapeño? We already have a watch for "OpenAI Jalapeño chip initial production deployment" by late 2026. This is perfect. Let's resolve the thread: `019f0679-f319-75c7-b35d-6dea5ba6b6d4` (Long-Term Impact of Custom Silicon on Nvidia's Pricing Power and Margins). Let's call `resolve_thread` for it.

Awesome. Now let's register a watch for Qualcomm's data center products. Let's see: - Title: "Qualcomm HBC Gen 1 and AI250 commercial sampling" - Cardinality: `one_shot` - Watch type: `dated_catalyst` - Fire date: `2027-06-15T00:00:00Z` (Mid-2027) - Entity: `QCOM` - Description: "Monitor Qualcomm's progress toward commercial sampling of its High Bandwidth Compute (HBC) Gen 1 technology with the AI250 accelerator, which aims to bypass HBM memory bottlenecks." - Topic ID: `019e95ad-bd47-7cf5-bd57-eb159d26bbbe` - Cycle ID: `469f78ba-d942-4d68-9f82-821e95c03656` Let's register this watch.

This is fantastic. Let's register another watch for the commercial launch of Qualcomm's Dragonfly C1000 CPU with Meta. - Title: "Qualcomm Dragonfly C1000 commercial availability" - Cardinality: `one_shot` - Watch type: `dated_catalyst` - Fire date: `2028-01-15T00:00:00Z` (Early 2028) - Entity: `QCOM` - Description: "Monitor the official commercial release and deployment of Qualcomm's 250+ core Dragonfly C1000 CPU in Meta's next-generation server fleet." - Topic ID: `019e95ad-bd47-7cf5-bd57-eb159d26bbbe` - Cycle ID: `469f78ba-d942-4d68-9f82-821e95c03656` Let's register this watch.

Let's check if there are any other topics or findings we should update. Wait, let's look at the remaining notes: - `big-tech-capex-reaches-710b-in-2026` (Big Tech's AI Capex Reaches Historic Scale as Hyperscalers Guide Up to $725B in 2026) This note mentions that Big Tech capex reaches historic scale as hyperscalers guide up to $725B in 2026. In our findings, we have now added that Nvidia projected AI infrastructure spending to reach $3 to $4 trillion annually by the end of the decade, with hyperscale capex expected to exceed $1 trillion by 2027. This is a very important update to the capex story. But since we already captured it in the main Nvidia note `nvidia-record-q1-results-and-trillion-dollar-order-book`, we don't necessarily need to create or heavily modify `big-tech-capex-reaches-710b-in-2026` unless we want to link them or update the numbers there. Let's see if we should leave it as is or do a small update. Actually, the main question "Is Nvidia's AI capex story still intact?" is fully answered by our updates to: 1. `nvidia-record-q1-results-and-trillion-dollar-order-book` (which is the direct subject of the brief) 2. `custom-silicon-and-datacenter-hardware-competition` (which provides the long-term counter-narrative and competitive threats) Let's double-check if there are any other tools or actions needed. We have: 1. Called `list_threads` to see what the user wants pursued. 2. Gathered and confirmed evidence using `web_search`, `web_fetch`, and `market_view`. 3. Updated two existing notes with stable slugs (`nvidia-record-q1-results-and-trillion-dollar-order-book` and `custom-silicon-and-datacenter-hardware-competition`), grounding them in concrete evidence (verbatim quotes, URLs, and `/markets` URLs). 4. Resolved an active question thread (`019f0679-f319-75c7-b35d-6dea5ba6b6d4`). 5. Registered two new forward-looking watches for Qualcomm's upcoming data center products. Let's call `finish_cycle` to complete this research cycle. This is the only way to end the cycle. Let's do that!

I have completed the research cycle on whether Nvidia's AI capex story remains intact. Here is a summary of the findings and updates from this cycle: ### 1. **Nvidia's AI Capex Story is Exceptionally Intact (Near-to-Mid Term)** Our public markets view and Nvidia's Q1 FY2027 results (reported May 20, 2026) show that the AI infrastructure demand curve remains in a "parabolic" growth phase. * **Blockbuster Earnings**: Nvidia reported record-shattering quarterly revenue of **$81.61 billion** (up 85.2% YoY and 20% sequentially) and net income of **$58.32 billion**. Data Center revenue reached **$75 billion** (representing ~92% of Nvidia's business). * **Unprecedented Pricing Power**: H100 rental prices have increased by **20% year-to-date**, and A100 cloud pricing has risen nearly **15%**, demonstrating that demand continues to outstrip supply, even for older-generation architectures. * **Vera CPU & Agentic TAM**: Nvidia launched **Vera**, its custom CPU purpose-built to handle agentic AI orchestration workloads. The company expects **$20 billion in standalone CPU revenue in FY2027**, opening up a brand-new $200 billion addressable market. * **Massive Capital Returns**: Backed by **$49 billion in quarterly free cash flow**, Nvidia announced a massive new **$80 billion share buyback program** and increased its dividend to $0.25 per share. * **Future Capex Projections**: Management highlighted that while hyperscaler capex is on track to exceed $1 trillion by 2027, the proliferation of agentic AI is expected to drive annual AI infrastructure spending to **$3 to $4 trillion by the end of the decade**. ### 2. **Emerging Long-Term Competitive Threats & Supply Chain Risks** While the short-term outlook is robust, significant competitive developments occurred in late June 2026, targeting Nvidia's core moats: * **OpenAI & Broadcom "Jalapeño" Chip**: On June 24, 2026, OpenAI unveiled its first custom AI chip, **Jalapeño** (an "Intelligence Processor" optimized specifically for LLM inference). Developed in an ultra-fast nine-month cycle, it is running GPT-5.3-Codex-Spark in the lab and is set to deploy at **gigawatt scale with Microsoft and other partners starting in late 2026**. * **Qualcomm & Meta Partnership**: On June 25, 2026, Qualcomm announced its entry into the data center CPU and inference market with the **Dragonfly C1000 CPU** (250+ custom Oryon cores, 2x performance-per-watt advantage) and secured a **multi-year deployment partnership with Meta** to power Meta's next-generation server fleet. * **Vera Rubin Supply Chain Risks**: TrendForce reported that the next-generation Vera Rubin platform faces shipment delay risks due to HBM4 validation and liquid cooling optimizations, lowering Rubin's projected 2026 shipment mix from 29% to 22%. However, the gap will be filled by the highly mature **Blackwell platform (GB300/B300), which is now projected to dominate at over 70% of high-end GPU shipments in 2026**. These updates have been compiled into the following standing findings: * **[[nvidia-record-q1-results-and-trillion-dollar-order-book]]** (Nvidia's AI Capex Story Remains Intact Amid Blockbuster Q1 Results, Pricing Power, and Vera CPU Launch) * **[[custom-silicon-and-datacenter-hardware-competition]]** (Custom Silicon and Data Center Hardware Competition Escalates to Challenge Nvidia's Moat) I have also resolved the question thread regarding the long-term impact of custom silicon and registered two new watches to track Qualcomm's data center sampling (mid-2027) and deployment with Meta (early 2028).