Cole (@Fortifiedvc) header
Cole (@Fortifiedvc) profile picture

AI Infra Finance • DC Builder • Structured Credit/CRE/CMBS • ex-MS & DB. 100x Agency to Scale... Not Financial Advice.

Global
Joined December 2021
Cole retweeted
The "Rack Spread" is unfolding, token prices are falling while GPU prices climb Change since mid-July: - B300 GPU rentals up 106% - B200 up 66% - H100 up 17% - Average token prices down 58% Charts of the Week: a16z.news/p/charts-of-the-we…
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Expert Takeaways: Nebius > Nebius operates an auction-driven cluster-access pricing model that drives up pricing levels by ~20% through competitive bidding. > Nebius requires 60–65% upfront contract payments, providing strong protection compared to debt-heavy peers like CoreWeave (facing up to 15% interest on new debt). > Short-term spot capacity fetches $40–50M ACV per megawatt (potentially up to $60M with auction uplift) vs. $20–25M for medium-term deals. > Tight supply for latest-generation GPUs through at least mid-2028 supports reserving 2027 capacity for high-margin spot workloads. > Meta and SpaceX control >1M GPUs and plan to deploy 25k–50k units monthly, pulling bare-metal contracts away from neoclouds. > Open-source models deliver comparable results at 70–80% lower cost, eroding OpenAI and Anthropic enterprise revenue. > Gartner projects >80% of independent neoclouds will fail by 2030 due to a K-shaped market favoring GB300/Vera-class hardware over older GPUs. > Nebius is insulated from cascading neocloud defaults because its core clients (Microsoft, Meta) are AA/AAA-rated, unlike BB-rated frontier labs. > High-end hardware (GB200/GB300) is shifting to inference workloads, which offer 4–8× higher margins than training. > Micron predicts HBM3/HBM4 memory shortages beyond 2028, while Microsoft’s 300,000 internal Maia ASICs displace demand for 300,000+ Nvidia GPUs. $NBIS $GOOGL $META $MSFT $AMZN
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There is nothing special about this pullback. Much of the panic surrounding neoclouds, AI capital expenditures, and the sustainability of the infrastructure buildout is simply the market searching for explanations for falling stock prices. When AI stocks were rising, record capex was evidence of extraordinary demand. When those same stocks started falling, suddenly the same spending became evidence of an impending financial disaster. One fact with two interpretations that depend entirely on the price action of the market. Go back to August 1998. The technology bull market had been running for about three years.Amid fallout from the Asian financial crisis and Russian ruble crisis, earnings expectations were deteriorating, valuations were elevated, and investors were becoming increasingly concerned about unprofitable Internet companies. On August 6, the New York Times published an article titled "Market Gyrations May Point to Shift in Investor Strategy." One fund manager declared, "Boring is going to outperform sexy." Investors were supposedly abandoning momentum and speculative technology shares in favor of profitable businesses, balance sheets, dividends, and traditional valuations. Russia defaulted on its debt. The Asian financial crisis was spreading internationally. The yen carry trade had imploded as the USD plunged 8% against the yen in a single day. US embassies were being bombed. President Clinton ordered missile strikes against Afghanistan and Sudan while simultaneously facing a scandal that would result in his impeachment. Major financial institutions suffered enormous losses, and the spectacular collapse of Long-Term Capital Management threatened the stability of the global financial system. Corporate earnings forecasts were falling. Investors feared a U.S. recession. Many of the same technology companies that had driven the bull market were now leading the decline. Many of them had fallen 40-60% from their 1998 highs. Even the Federal Reserve's first interest-rate cut on September 29 initially disappointed investors. The Dow fell that day and plunged another 238 points the following session. The news seemed almost uniformly terrible. But the market didn't care forever. After a violent reversal in early October, improving confidence in corporate earnings, Japanese banking reforms, and a surprise emergency Fed cut on October 15 helped restore risk appetite. By November, the Dow was making new all-time highs. Internet stocks were exploding higher again. What had looked like the end of the internet trade was, within about a month, actually a correction preceding one of the most extraordinary speculative advances in stock-market history. In today’s market, Microsoft just reported 48% Azure growth. Google Cloud revenue more than doubled. Meta expects $135–145 billion in capex this year and has announced plans for a potentially record-sized $97.5 billion equity capital raise. If the market really was that concerned over capex spending, instead of using it as an excuse to explain the pullback, the market would have sold off on the META news. Anthropic has now filed its IPO registration statement. We have midterm elections approaching, another consequential round of earnings, and a Fed that just held rates steady even as another hike is widely anticipated in December. There are plenty of potential catalysts over the coming two months. More importantly, this does not resemble the sentiment backdrop of a speculative bubble climax. Generational bull markets don't die midway through a basing period, but typically after euphoric saturation and a parabolic rally in leading names. Consensus on AI is deeply divided. Being loudly anti-AI has practically become fashionable. Some AI critics have even built enormous audiences around the idea that the economics of the industry are unsustainable. Plenty of investors seem almost eager to watch the entire trade collapse. That isn't the sentiment or narrative around which tops are typically made. The Internet trade didn't end in the panic of 1998. It ended after the extraordinary acceleration of 1999 and early 2000 when being bearish was the market equivalent of wearing a dunce cap. History never repeats perfectly, and today's rate environment is very different. But I think the resemblance in investor psychology is striking. I’d be genuinely surprised if we don't have at least one more months-long rally into new highs during this cycle. Whether it begins into the midterms, after the elections, around Anthropic's anticipated listing, or following further earnings confirmation, I suspect this correction will eventually look more like an interruption in a generational bull market than the bursting of a "bubble." The $NDX took four months to bottom in 1998. With the exception of a handful of leaders, most stocks that are holding up have been basing out since the May-July period. We could certainly go lower, but most of the signs point to another new high before this cycle rolls over. However, I’d place the odds of any additional powerful rallies afterward as increasingly unlikely given the fact we are already about to enter the fifth year of this bull market. I'd be careful about buying the dips next year, at least with meaningful size.
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A new way of looking at GPU depreciation schedules for $NBIS. If the idea is compute contract lengths should shorten, benchmarking residual value by on-demand payback is better. Older GPUs do better in these short term contracts as well.
Replying to @OrnnExchange
Neoclouds effectively pay for clusters twice - first in principal and interest, then in massive discounts on 5-year take-or-pay contracts. Our research covering 850 days of H100 prices shows how much upside neoclouds could be capturing by selling on-demand:
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Citizens: Neoclouds "CoreWeave has the largest contracted platform and the most future capacity to reprice; Nebius already shows the rate reset in agreements signed at $20–$25 million/MW, with customers prepaying 50–60% of the associated capex; and IREN shows the progression from roughly $10 million/MW on its original Microsoft agreement to above $20 million on newer contracts." "We are more positive on the Neocloud business model in the near-to-intermediate term. The equities and credit have repriced around the capital required to deliver the build, but demand continues to exceed available supply, delivery remains back-end loaded, and the newest contracts are being signed at higher rates." $NBIS $IREN $CRWV
Citizens out this morning saying buy the dip on Neoclouds! “Every delayed MW increases the value of existing energized capacity, in our view, strengthening the positioning of Coreweave, Nebius, and IREN as the next round of capacity is contracted.” $NBIS $IREN $CRWV
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GPU RENTAL PRICE HIKES BY CLOUD PROVIDERS: • AWS: Q3 increase of 20% • Nebius: cumulative 50% increase • CoreWeave: 25% across all SKUs $AMZN $MSFT $GOOGL $CRWV $NBIS $IREN $DOCN
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Revenue per GPU can increase as token prices decline if per GPU token throughput increases enough. So both Anthropic revenue *and* margins can go up as token prices go down *if* GPU prices go up less than the product of (token price decline * per GPU throughput increase). But I have super enjoyed all the commentary to the contrary!
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As someone with a portfolio of energized land assets here is what I am seeing: 1. Neoclouds are disorganized and poorly capitalized. Some are definitely better than others however. 2. Hyperscalers are intractable, bureaucratic organizations that take 3 months to do an NDA and want 18mo escrow periods. We built our portfolio by competing against these terms because of our speed and simplicity. The more future assets orgs like ours win, the bigger the problem for the hyperscalers downstream (see 3). 3. There are delays in the existing pipeline that will catch people off guard in 2027. Hyperacalers will (obviously) react by focusing on their own internal compute needs over any third party. If the third party is a model company, they will tell them to go through their model router where they will also take a non-trivial vig. Them telling Ant they have no compute for them (rumored in Ant’s S-1) if true is a huge tell that this is already happening. All of this is to say that it does look like there will be a lot of partially stranded compute and compute sitting in inventory in 2027 than is currently forecasted. This is bought and paid for but effectively underearning (below total cost of capital) or collecting dust. We see this as true for everyone - model companies, hyperscalers, neoclouds except ONE (you can guess which one). This dislocation will benefit two kinds of orgs: the non-bureaucratic big scalers who can build industrial scale quickly and the nimble, well capitalized players feeding them. 2027 will be a turbulent year because it will clear out a bunch of wrong/bad bets. It will also be a consolidation year for a few.
Replying to @Yuchenj_UW
I think we’re going to see a lot of stranded compute in partially complete data centers
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Renting Nvidia’s H100 costs 45% more than it did in December. It went on sale in 2022, and two newer generations have come out since. Yet, demand for compute is so far ahead of supply that older GPUs are getting more expensive.
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Cole retweeted
Zooming out, GPUs are still renting ahead of a standard 6-year depreciation schedule Rental price vs. schedule: - H200: +143% - B200: +111% - RTX PRO 6000: +73% - H100: +54% - A100: +9% Most of the gap opened up after April, when token demand took off Charts of the Week: a16z.news/p/charts-of-the-we…
GPUs are aging like fine wine, with rental rates up across the board since January 1st Approximate change YTD: - H200: +160% - B200: +120% - RTX PRO 6000: +65% - H100: +35% Even the 6-year-old A100 rents for more than it did at the start of the year Charts of the Week: a16z.news/p/charts-of-the-we…
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Cole retweeted
GPUs are aging like fine wine, with rental rates up across the board since January 1st Approximate change YTD: - H200: +160% - B200: +120% - RTX PRO 6000: +65% - H100: +35% Even the 6-year-old A100 rents for more than it did at the start of the year Charts of the Week: a16z.news/p/charts-of-the-we…
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At @OrnnExchange, we've always been focused on incredible people, innovative product and compressing timelines. We are taking the next steps to push AI compute markets forward and this team has always been by our side. Excited to continue building alongside @cdixon and the @a16zfrontier team!
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$NBIS SECURES $3.5 BILLION FINANCING FACILITY FROM CITI Nebius announced a new senior secured credit facility to fund its global AI data center expansion and GPU purchases. The facility has a 364-day maturity, with interest starting at SOFR + 2.75% and potentially rising to SOFR + 3.50%. Nebius has more than $40 billion in long-term contracts with investment-grade customers, which could support additional asset-backed financing as it expands AI capacity in 2027 and beyond.
Asked how far $NVDA would go to financially backstop neoclouds, or even bail one out, Jensen said: “We invested in them... that's different than backing them” He says neoclouds are “completely sold out” & expects them to secure the working capital they need h/t @TomMackenzieTV
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Public investors see the supply side of AI (the chips and the hyperscalers), and little of the demand side, because the demand lives in private companies (as my colleague @jrichlive often says). Since April, token usage on @Vercel's AI Gateway has grown almost 8x, and spend more than 3x’d. Prices fell by more than half during that time, and developers bought nearly eight times as much. In 30 years, I haven't seen demand like this.
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Cole retweeted
AI builders need computing capacity they can put to work sooner. We introduced DSX POD at NVIDIA GTC Berlin: AI factories integrated and tested before delivery, enabling deployment at prepared sites in as little as 14 days.
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SCOOP: Fireworks AI is seeking to raise fresh funding at a valuation between $30 billion and $40 billion, a dramatic jump just months after the AI-infrastructure startup was valued at $17.5 billion. businessinsider.com/firework…
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$META +3% AH. >Revenue $64.6B beat (guide was $61-64B) >FY capex floor raised: $135-145B vs $130-145B, midpoint $140B. >Q4 math: YTD capex (incl. finance leases) is $85.8B >Raised capex guidance implies $49-59Bin Q4, ~$54B at midpoint, +55% q/q. "Our AI investments are already delivering substantial incremental advertising revenue through stronger engagement, better recommendations, and more efficient monetization."
$META reports after the close. We think 3Q26 earnings could be positive read through for $CLSK & $APLD (among all PSPs and neos) - Look for Muse monetization and potential compute expansions to support it - FY 2026 capex guide is currently $130-145B - FY 2027 consensus capex guide is $193B Muse early adoption looks strong with 10.9M downloads and ~2.5M DAUs, much faster growth than other launches (although caveats being Muse launched on IOS and Android at once while ChatGPT, Claude and Grok were initially IOS only, and it was heavily promoted taking up most of Metas house-ad impressions). DAU durability is an open question due to this heavy marketing push. Lot of focus on Muse's monetization path and compute needed to support it, which is relevant for $CLSK which already has a 20-year lease with Meta at Sandersville (175MWs), and a LOI/exclusivity for 885MWs in its TX portfolio. Commentary supporting more 3P leases of capacity would be positive and would support lease execution of this additional power. Would be good to hear that Meta is back focused on utilizing its compute in-house rather than re-selling excess. Meta is also expected to come to debt markets shortly after earnings to fund capex plans, a smooth process could support their ability to keep expanding capacity via 3P leases (CLSK). It is also believed that APLD's two newest leases are with Meta (one unnamed hyperscaler), 300MW in Louisiana and 300MWs in North Dakota. Although this is unconfirmed. Also a potential beneficiary around commentary from Meta around wanting more 3P compute.
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Cole retweeted
Inference is a beautiful business. deepseek reports 155T tokens/day from one inference cluster at $38/gpu-hr. I estimate their cluster at ~5 MW, implying ~$160M/MW/year in API revenue and 84–92% margins after $3–6/GPU-hour rent working assumptions: 96% input-cache hits, ~107 input token/output token ratio -> ~$14.35 revenue per billion tokens at off-peak prices. working backwards from 155T tok/day, 60,000 uncached input tok/sec/gpu prefill + 14,000 output tok/sec/gpu decode, each two-GPU pair handles approximately 1.5m input + 14k output tokens/sec -> 2400 gpus. on blackwell hardware I assume 2 kW/gpu including external networking, cache storage, etc. No wonder everyone wants be part of the token flow / bid up GPUs :)
🚀 Introducing DeepInfer, our in-house inference framework, now fully open source! Powering DeepSeek-V4.1-Flash at scale with high throughput and low latency. We’re sharing our production stack to help the community lower compute costs, reduce energy use, and make AI more affordable. 🔗 github.com/deepseek-ai/DeepI… 1/4
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Our $DESKB300 sent to the moon due to open source inference demand. @ComputeDesk
Blackwell Ultra (B300) GPU rental prices up 17 consecutive days to a new all-time high, according to Compute Desk's index of verified transactions from U.S. neoclouds.
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Blackwell Ultra (B300) GPU rental prices up 17 consecutive days to a new all-time high, according to Compute Desk's index of verified transactions from U.S. neoclouds.
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