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Nvidia CORP

NVDA

251 stories

$4.6T Market cap · 2026-11-06

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@convequity 1 click

Convequity on X

Despite investor doubts, $IREN is worth a small position. The shares have fallen about 17% from their 22 Sep close. The equipment IREN had ordered at 30 June is covered by the cash, committed GPU financing and prepayments it reported on 27 Aug. In the June 2026 quarter customers funded most of its capex. On signed contracts the shares are priced about where $CRWV is. The main risk is that IREN runs GPU clouds worse than its peers. 1. IREN guided FY27 capex (Jul 2026–Jun 2027) at $25–30B on its 27 Aug results call. Its enterprise value is $14.6B at the 5 Oct close. IREN's FY26 results show revenue of $0.7B, of which $0.58B was bitcoin mining. IREN expects to have shut mining down by the end of December 2026. 2. At 30 Jun 2026 IREN had $13.8B of commitments for GPUs and site work, almost all payable by 30 Jun 2027, per its annual report. Orders placed after 30 June are not in that figure. On 27 Aug IREN put its existing cash, committed GPU financing and customer prepayments at about $14B. That covers the 30 June commitments. 3. The other $11–16B of the capex guide is not yet funded. Management targets about $8B more in GPU financing and prepayments for new GPU capacity, and that funding comes with new customer contracts. IREN says it is in late-stage talks for a large share of 2027 capacity. It has not announced any signed contract for that new 2027 capacity. The rest would come from data-center debt, operating cash flow and corporate funding, which includes selling shares. By 14 Aug 2026 IREN had sold about $2.5B of shares under its $6B ATM programme, leaving about $3.5B at that date, per its annual report. It has not reported any sale since. 4. On signed contracts, IREN is priced close to CRWV. On our ABBX dashboard, enterprise value is 0.88x contract value for IREN, 0.74x for CRWV and 1.60x for $NBIS. The contract values are company-reported, and each company measures them differently. IREN reports about $16.6B, of which about $5.1B is cloud service contracts and about $11.4B is GPU lease contracts. CRWV reports a $104.2B revenue backlog. NBIS reports $37.5B of remaining performance obligations. On 27 Aug IREN said its 2026 capacity was largely sold out. It had $4B of contracted annualised revenue run-rate (ARR) for 2026 capacity, which it earns once that capacity is delivered and accepted. $1B of ARR was already operating. EV is about 3.7x the contracted $4B. 5. In the June 2026 quarter, IREN's customers funded most of its capex. On our ABBX dashboard, customer prepayments and deferred revenue covered 87% of IREN's cash capex in that quarter ($1.72B of $1.98B). The same measure was 21% at NBIS and 12% at CRWV. Working-capital inflows covered 90% of IREN's capex and 36% of NBIS's. CRWV's working capital was an outflow equal to 8% of its capex. More than half of IREN's customer prepayments came under the $MSFT contract. At 30 Jun 2026, $1.01B of IREN's $1.84B of deferred revenue sat in the subsidiary that holds the GPUs for the MSFT contract, per its annual report. IREN said on 27 Aug that $3.6B of GPU financing plus customer prepayments fund about 96% of the GPU capex for the MSFT contract. IREN also said its recent contracts carry prepayments of 45–55% of GPU capex. So in that quarter customer cash, not new debt or shares, paid for most of IREN's capex. At NBIS and CRWV it paid for a small share. 6. Operations are the weak point. Some people are questioning the quality of the GPU cloud service IREN delivers to end customers. We share the concern, and it is not new to us. We recorded it in our 1Q26 rebalancing meeting and again in 2Q26 and 3Q26. One of our biggest concerns on IREN is that the CEO treats software as easy, low-value work next to power, land and data centres. That includes the orchestration software that schedules customers' jobs and manages the GPUs. We expected this to slow IREN's growth, not to threaten the business, for three reasons. (A) In our view the bottleneck in AI infrastructure today is powered capacity, not the know-how to run GPU fleets. IREN said on 27 Aug that its recent 3-year contracts price above $20M of revenue per MW of computing capacity. It estimates about a 2-year payback on the GPUs and related equipment. It also said its 2026 capacity is largely sold out. (B) Hyperscalers and other bulk buyers of IREN's capacity can manage and optimise GPUs better than IREN can. What they need from IREN is powered GPU data centres delivered on time. MSFT's $9.7B contract is for GB300 GPUs in four 50MW buildings. MSFT accepted the first, Horizon 1, in August 2026. IREN targets Horizons 2–4 in the December quarter. (C) $NVDA is partnering with IREN and is trying to make running large GPU fleets more standard and simpler. In our view NVDA wants standard fleet-management software so that more companies can run its GPUs well, which makes its chips easier to buy and use. On 7 May 2026 NVDA signed a five-year, $3.4B managed GPU cloud contract with IREN that uses Mirantis orchestration software. The same day it announced a partnership to deploy up to 5GW on NVDA's DSX reference designs. DSX is NVDA's standard set of designs and software for building and running AI data centres. In its 31 May 2026 DSX release, NVDA says the DSX OS software handles tasks such as keeping GPUs healthy, scheduling jobs and running several customers on one cluster. The same release names IREN, CRWV and NBIS among the cloud partners deploying core parts of DSX. The risk in (C) is that IREN's CEO may be too optimistic about how capable NVDA will be at this and how soon. 7. IREN is buying software and hiring managers to run its cloud better. It bought Mirantis, a cloud software company with more than 1,500 enterprise customers, on 4 Aug 2026. IREN said at completion that it paid about 12.6M shares plus about $40M. In July 2026 it hired a product chief from $ORCL (its cloud unit), a data-center development chief from $GOOGL and CyrusOne, and a security chief from $NTNX. We found no hire of a head of cloud operations. We would change our view in three cases. First, if a Horizon delivery for MSFT is missed or rejected. Second, if the Q1 FY27 report arrives with no new contract for 2027 capacity announced. Third, if IREN's weak end-user experience turns out to come from its infrastructure, meaning power, cooling, networking, storage or the GPU hardware itself, and not just from its orchestration software. The third matters because bulk buyers can replace IREN's software with their own, but they depend on IREN for the site and the hardware.
@convequity

Convequity on X

$NVDA is still the cheapest way to produce AI tokens when 150 or more users share one batch. When one user wants the fastest possible answer, the economics change. Our Cerebras note puts the rule in two parts. 1. NVIDIA is the cheapest token factory when 150+ concurrent users share one batch and each user gets a moderate speed. 2. To maximise speed for a single user, the batch has to shrink, so the system's total output falls. That loses money per token unless the faster answers are sold at a higher price. Cerebras ($CRBS) sits at the other end. Its wafer-scale chip gives fast answers to a single user and reaches its best efficiency at 4 users. Like a taxi, it is quick and direct, but it has fewer seats to spread the cost across. The two also differ in how much room each has left to improve. SRAM-based designs like Cerebras have already captured most of their performance upside. GPU fleets often run at low compute utilization today, and that gap is room for future gains and economies of scale, not a permanent cost. So fast inference only pays if customers will pay more for speed. Our view is that a sizeable portion of the market will pay a premium for speed.

The Next Consumer is a Computer

Meta’s Muse illustrates how persistent AI agents shift compute from per-query to per-user, driving heavier GPU, CPU and memory demand.

@aleabitoreddit 1 click

Serenity on X

Bro, $AMZN semi ETF portfolio is probably going to end up more compelling than what $NVDA owns... Today Amazon signed a $49.8M private placement into PCB maker Gold Circuit Electronics (2368). So now Amazon has ownership/warrants in: - $AAOI - Alchip - $MRVL (Celestial) - $ALAB - $CRDO - $JBL - $FLEX - $STM - $CBRS - $GNRC - $FN - TD SYNNEX - $QCOM - Gold Circuit Electronics And others.. If we look at the private placement amount for GCE in speciifc, it's like .36% of the company... Kinda small financially, meaningful strategically. Esp. since there were claims that GCE supplies ASIC-server PCBs to the four major hyperscaler CSPs... Regardless it's pretty funny to see Amazon to Nvidia start to own all the worlds leading companies. Since Amazon has exposure to the entire supply chain like PCBs now, optical fabric with Celestial, lasers with $AAOI, assembly from $FN to $JBL, ASIC partners like $QCOM / ALchip.
@aleabitoreddit

Serenity on X

Everyone is asking "Where is Serenity" or "Who is Serenity". But nobody is asking... "How is Serenity"? I do read things from $AMD $8.2B acquisition of World Labs... but feeling pretty sick right now, so taking a little break. I remember saying physical AI + world models would major shift way back when, so maybe I should have invested in private companies at the time... Apart from that... other interesting news: - Some channel checks from ECOC was that $NVDA apparently secured 50% of $LITE Greensboro UHP laser capacity? And possibly contracts that allow them to secure the remaining capacity per Barclays. That's $5B in lasers (annual capacity)... so it's hilarious to see Nvidia go out and bottleneck the rest of the industry by doing this. But this just puts more strategic value on other merchant laser suppliers + more visibility for Lumentum. It's kinda game theory over allocation, since if you secure all the HBM, lasers, and others it inadvertently makes it much harder for competitors to scale their programs. - Then there's your massive $150B Nvidia authorized buybacks (just look at $AAPL when they did buybacks..) They're printing too much. - What's also interesting is that Samsung Electro-Mechanics is expanding their FC-BGA substrate capacity today... but customers are the one funding this. I also remembered $MRVL in SEC filings cited large body substrates as one of the core bottlenecks of their program (alongside $TSM sole source dependencies). So they also went out and did some other expansion agreements with related companies like AT&S recently. - OpenAI delaying Astra-6.1 October release over safety concerns just now. Nvidia also happened to launch an AI safety platform. I don't think this is meaningfully bearish that the models are just getting 2 good.
@convequity

Convequity on X

The $PLTR and $NVDA work on Nemotron, NVIDIA's open model family, is still under the radar, unlike partnerships that promise more than they deliver. In our view it could be industry-transforming, because each side needs the other: Nemotron is the Western open model that fits, and Palantir is the only vendor that can put a model into an enterprise securely, safely and privacy-first, and limit it to what each person may see and change, which is why AIP, Palantir's AI platform, took hold and why NVIDIA needs Palantir. Palantir has no proprietary model and leans on closed models from OpenAI and Anthropic. Chinese open models are almost certainly off the table for a U.S. government contractor. On August 26 Jensen Huang said every major company needs its own proprietary AI, and open models make that possible. On June 29 Palantir launched an engine that runs custom Nemotron models for U.S. agencies and critical industries on networks cut off from the outside. The customer can train this American open model further on its own data and keep the weights, the trained model. On September 10 they announced a supply-chain stack, first on NVIDIA's own supply chain. On July 14 NVIDIA said other companies already specialize Nemotron for their own domains. The test is whether that stack moves from NVIDIA to named customers in manufacturing, energy, healthcare, automotive or aerospace.

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