--- title: "H100: what it means · The AI Compute Race · DRYBURGH" source: https://dryburgh.com/vol1/glossary/h100 description: "H100: NVIDIA's accelerator of the Hopper generation, the chip of the fleets of 2023 and 2024. Its rent and resale are the test of destructive finance." --- # H100 What does “H100” mean? H100NVIDIA’s accelerator of the Hopper generation, the chip of the fleets of 2023 and 2024. Its rent and resale are the test of destructive finance. *Chapters 4, 12.* From *The AI Compute Race*. [Read the book](https://dryburgh.com/vol1#buy) ## Where the book uses it - [Chapter 4 — One Rack](https://dryburgh.com/vol1/notes/chapter-4)How a datacenter is actually built, from a converted factory in Memphis to a greenfield campus in Texas, and what the clock from first ground to first power really measures. - [Chapter 12 — Cross-Examination](https://dryburgh.com/vol1/notes/chapter-12)The book’s own thesis put on trial: five claims, each scored against the record and given a dated test that could prove it wrong. ## Where the record uses it - Dated test [Chapter 12, claim 5, the first fleet reading, rent, due 31 December 2027](https://dryburgh.com/vol1/tests#2027-28) - Dated test [Chapter 12, claim 5, the second fleet reading, utilization, due 31 December 2027](https://dryburgh.com/vol1/tests#2027-29) - Dated test [Chapter 12, claim 5, the third fleet reading, resale, due 31 December 2027](https://dryburgh.com/vol1/tests#2027-30) ## Sources that use it - Karen Hao, *Empire of AI: Dreams and Nightmares in Sam Altman’s OpenAI* (Penguin Press, 2025), ch. 5 “Scale of Ambition”, ch. 12 “Plundered Earth” and the Epilogue (the Microsoft–OpenAI supercomputer “phases”, from an internal OpenAI document: Phase 1 West Des Moines, 10,000 V100s, GPT-3; Phase 2 Iowa, 18,000→~25,000 A100s, GPT-4; Phase 3 Arizona, hundreds of thousands of H100s; Phase 4 Wisconsin, ~$10bn, B100s; Phase 5 ~$100bn; ch. 5 on the post-ChatGPT funding of Chinese models; the book takes only the environmental filing’s 169 liters a second for the Cerrillos site, not Hao’s population comparison, which she later retracted; the quotation “In AI, whoever has the biggest computer gets the most benefits” is read in the full text of the book, not on the publisher’s page the URL names; in the Epilogue, Uruguay is told as the campaigner Daniel Pena’s account in Hao’s words: the environmental ministry “quietly approved the project, revealing the decision only after the thirty-day public contestation window was over, he says”; ch. 5, on Chinese funding after ChatGPT: companies and investors began funding the development of gargantuan models “with gusto”, having “seen enough evidence that they could recoup their investments through commercial applications”; ch. 5, on Microsoft’s investment: “$1 billion investment came with $1 billion expectations; OpenAI was on the clock to deliver something that would justify the expense”; ch. 12, an OpenAI employee on Phase 5: “we’re running out of land and power”; ch. 5, Hao’s own sentence, reporting without quotation marks a Chinese AI researcher’s analysis of China before ChatGPT: no team “would get $1 billion, let alone ten times more, to develop a massively expensive technology without an articulated vision of exactly what it would look like and what it would be good for”; ch. 5, her conclusion: “Everything OpenAI did” … “was the opposite of inevitable” (everything lower-case mid-sentence in the source); ch. 6, “Ascension”, on a memo Altman sent to the company in late 2019, quoted from her copy of it, her note reading “Copy of the memo.”: OpenAI needed to “be number one” by the end of 2020 in four categories, which she lists as technical results, compute, money to acquire more compute, and preparation, and “We still need many more 10x leaps to get to AGI”; the Prologue, “A Run for the Throne”: the empires “seize and extract precious resources to feed their vision of artificial intelligence: the work of artists and writers; the data of countless individuals posting about their experiences and observations online; the land, energy, and water required to house and run massive data centers and supercomputers” and “exploit the labor of people globally to clean, tabulate, and prepare that data”; ch. 12, “Plundered Earth”, on Cerrillos: “In late 2019, as communities across the country began to hold referendums in response to the movement to reform local and national politics, MOSACAT piggybacked on the referendum in Cerrillos to add a question about whether residents agreed for Google to build a facility that would consume so much of the community’s water”; “In December 2019, MOSACAT won; the referendum to build the data center was rejected with a slim majority of the vote.”; ch. 7, “Science in Captivity”, on China after GPT-3, in a sentence whose note cites Ding and Xiao: “In China, GPT-3 similarly piqued intensified interest in large-scale models”, the Chinese giants treating the direction “as a novel addition to their research repertoire, not a new singular path of AI development warranting the suspension of their other projects”; the sentence is Brockman’s, in Hao’s own words, “Brockman told me in 2019,” in the chapter on scale; Brockman’s title at the time of her reporting, from her MIT Technology Review profile of OpenAI of 17 February 2020, “The messy, secretive reality behind OpenAI’s bid to save the world”, whose caption reads “Greg Brockman, co-founder and CTO”; the same profile’s caption gives “Dario Amodei, research director” and its text “the policy team, especially Jack Clark, the director”, their titles at the time of her 2019 reporting; ch. 12, the Phase 1 code names: “Microsoft code-named the Phase 1 supercomputer Odyssey; OpenAI called it Owl”; ch. 5, on the machine: “Microsoft was about to deliver a new supercomputer to OpenAI as part of its investment, with ten thousand Nvidia V100s”; ch. 5 notes: “Author interview with Dario Amodei, August 2019” and “Author interview with Jack Clark, August 2019”; Notes, “Author interview with Brockman, August 2019”; ch. 5, the run: “Amodei wanted to use all of those chips, all at once”, “Before then, models were already considered large-scale if trained on a few dozen chips”; ch. 5: “Where Amodei saw a larger language model as a necessary prerequisite for AI safety research, Altman saw its potential for fulfilling OpenAI’s promise to Microsoft”; ch. 6, Kaplan: “a close friend from grad school and former roommate who worked part time at OpenAI and had led the discovery of scaling laws”; ch. 12, Phase 5: Altman was “casually floating the idea of the $100 billion supercomputer for Phase 5. After the blowout success of ChatGPT, Altman tempered his expectations”; ch. 5: “Not even in Silicon Valley did other companies and investors move until after ChatGPT to funnel unqualified sums into scaling. That included Google and DeepMind”; ch. 5, the date of the Chinese researcher’s analysis: “As ChatGPT swept the world by storm in early 2023”) [In the Sources](https://dryburgh.com/vol1/sources/book#hao-empire-ai) - Stephen Witt, *The Thinking Machine: Jensen Huang, Nvidia, and the World’s Most Coveted Microchip* (Viking, 2025; on the Nobu dinner, p. 194: “In late 2023, Huang met with Elon Musk and Oracle cofounder Larry Ellison for sushi at the Nobu restaurant in Palo Alto. Ellison and Musk had a collective net worth above $300 billion”) (Larry Ellison on a meal with Musk and Huang at the Nobu restaurant in Palo Alto in late 2023: “Elon and I were begging, I guess is the best way to describe it. An hour of sushi and begging”; a Caltech data-center administrator’s H100 delivery wait of “almost eighteen months” in early 2024, the professors unwilling to switch, “They’d rather wait for the hardware than switch away from CUDA”, ch. 16, p. 185; Witt’s per-chip power ladder for chips “in standard configurations”, p. 207 — A100 250 W, H100 350 W, B100 700 W, B200 1,000 W; the 2016 DGX box drew as much power as a clothes dryer and its 2024 successor enough for a single-family home, p. 207, the boxes “modular units that customers stacked into the long ‘superpods’” of the data center; a former US military official on seizing TSMC’s fabs — “These machines are insanely precise, and insanely fragile, down to a precision of one atom. What do you think’s going to happen to that machine if a missile goes off next to it?”, remote disabling, “I would say the Taiwanese engineer sabotage thing is not to be underestimated”; Deb Shoquist, who ran NVIDIA’s logistics, on what would happen in a war — orders transferred to Samsung and other partners, and “What would happen is everybody’s products would get dumbed down a click”; Morris Chang telling Nancy Pelosi in 2022 the US fab projects were “doomed to fail” and calling TSMC’s concentration Taiwan’s “silicon shield”, and his argument that “no national economy would suffer as much as China’s if TSMC went offline”, p. 218; “the problem that investors had once faced valuing Nvidia alone now applied to valuing the entire stock market”, p. 209, the last page of ch. 19; ch. 20, pp. 210–212: “Huang now had fifty-five” direct reports and “no designated successor”, p. 211, after the earnings of 21–22 February 2024; “a giant, GDP-sized bet on the capabilities of this single sixty-one-year-old man”, p. 212; on NVIDIA’s planning for Taiwan: Shoquist, “If something happens to Taiwan and TSMC, the ramifications are so large it’s almost like asking me what I’d do if California fell into the ocean”, and Huang, “I don’t want her spending one brain cell on trying to mitigate that, because it’s impossible for her to do so” (p. 217); on Morris Chang to TSMC employees at a TSMC function in late 2023: “in the semiconductor space, there is no globalization anymore. The priority is national security only” (p. 217, two quoted sentences either side of Witt’s attribution)). [In the Sources](https://dryburgh.com/vol1/sources/book#thinking-machine-witt) - Amazon Web Services, “Amazon EC2 Capacity Blocks for ML Pricing,” price page, as served on 27 October 2026 and as it stood on 24 December 2025 (the seller’s own posted rate for an accelerator reserved and paid for up front, not a price a buyer is shown to have paid; one H100 in a p5.48xlarge in US East, N. Virginia, $5.970 an accelerator-hour, $47.757 an instance-hour, against $3.933 and $31.464 on 24 December 2025; “Reservation prices are updated regularly based on trends in supply and demand for EC2 Capacity Blocks”; “The reservation fee is charged up front at the time you schedule the reservation”). [In the Sources](https://dryburgh.com/vol1/sources/company#aws-capacity-blocks-oct26) - CME Group and Silicon Data, “CME Group and Silicon Data to Launch Compute Futures on October 5 to Unlock New Way to Hedge AI Risks,” press release, 11 August 2026 (NYMEX-listed contracts, pending regulatory review; each a month’s rent on an Nvidia H100 or Blackwell B200, tracking Silicon Data’s GPU rental-price indexes; Keavey (“compute has become the currency of the AI age”) and Li (“a public, tradable reference price for the resource every AI system runs on”) quotes) [In the Sources](https://dryburgh.com/vol1/sources/company#cme-compute-futures) - CME Group, Special Executive Report SER-9785R, “UPDATE: Initial Listing of Two (2) Compute Futures Contracts - Silicon Data H100 Rental Index Futures and Silicon Data B200 Rental Index Futures,” 25 September 2026 (no initial listing date, the specification table giving it as to be determined; “Pending all relevant CFTC regulatory review periods”; “The Exchange will further advise regarding the specific effective date”; 730 GPU-hours a contract, quoted in U.S. dollars and cents per GPU-hour, financially settled). [In the Sources](https://dryburgh.com/vol1/sources/company#cme-ser-9785r-sep26) And 45 more: [search the Sources](https://dryburgh.com/vol1/sources). ## Related terms - [Destructive finance](https://dryburgh.com/vol1/glossary/destructive-finance) - [Accelerator](https://dryburgh.com/vol1/glossary/accelerator) - [Hopper](https://dryburgh.com/vol1/glossary/hopper) - [B200](https://dryburgh.com/vol1/glossary/b200) - [Blackwell](https://dryburgh.com/vol1/glossary/blackwell) - [Compute futures](https://dryburgh.com/vol1/glossary/compute-futures) - [H200](https://dryburgh.com/vol1/glossary/h200) - [Perpetual](https://dryburgh.com/vol1/glossary/perpetual) - [Abilene](https://dryburgh.com/vol1/glossary/abilene) - [122 days](https://dryburgh.com/vol1/glossary/122-days) - [Announced against energized](https://dryburgh.com/vol1/glossary/announced-against-energized) - [Campus ledger](https://dryburgh.com/vol1/glossary/campus-ledger) From the glossary of The AI Compute Race. - [Campuses](https://dryburgh.com/vol1/ledger) - [Tests](https://dryburgh.com/vol1/tests) - [Scorecard](https://dryburgh.com/vol1/scorecard) - [Data](https://dryburgh.com/vol1/data/releases) - [Chapter by chapter](https://dryburgh.com/vol1/companion) - [The record at a glance](https://dryburgh.com/vol1/observatory) - [The machine](https://dryburgh.com/vol1/machine) - [One campus, four futures](https://dryburgh.com/vol1/hyperion) - [Glossary](https://dryburgh.com/vol1/glossary) - [People](https://dryburgh.com/vol1/people) - [Sources](https://dryburgh.com/vol1/sources) - [Notes](https://dryburgh.com/vol1/notes) - [Where the book was wrong](https://dryburgh.com/vol1/corrections) - [Where its sources were wrong](https://dryburgh.com/corrections?book=vol1) - [The Paper](https://dryburgh.com/vol1/paper) - [Consent](https://dryburgh.com/vol1/consent) - [Who builds and pays](https://dryburgh.com/vol1/parties) *The AI Compute Race: Five Races, One Machine* is a book by Lee S. Dryburgh, the first volume of THE COMPUTE ECONOMY, published by Dryburgh, an imprint of Contestra OÜ, Tallinn, Estonia; its record closes on 8 November 2026. [About the book](https://dryburgh.com/vol1)[Tell me when it is out](https://dryburgh.com/vol1#notify)