Ornn

Headlines · 3

1. Oct 21
   DeepSeek's $38-per-GPU-hour theoretical ceiling tops the inference revenue ladder

   Tomasz Tunguz compares two new data points on inference economics: DeepSeek's published calculation of a theoretical maximum of $38 in revenue per GPU card-hour, and SpaceX's third-quarter report. Tunguz places those against a B200 spot rental price of $8.77 per card-hour settled on 2026-10-20 per the ORNN Compute Price Index, a $5.27 negotiated rate implied from SpaceX's S-1, and a derived realized AI revenue figure of $2.44 per card-hour from its 8-K. He notes every figure is an estimate: DeepSeek's number describes a single best cluster running its cheapest model at off-peak prices, not a fleet average, and SpaceX's realized revenue uses installed rather than utilized capacity. SpaceX CFO Bret Johnsen said on the Q3 2026 earnings call that new compute deployments are generating payback of less than a year at current pricing, while Tunguz also cites GPU rental prices doubling in six months, from $4.40 to $8.08 per card-hour, against faster falls in the price of intelligence.

   Tomasz Tunguz · 🔥 0
2. Oct 20
   CME compute futures delayed as GPU rental becomes a tradable contract

   Economic Observer, republished by 36Kr, reports that two compute futures designed by CME Group and Silicon Data on Nvidia H100 and B200 rental prices were originally slated to list on NYMEX on Oct 5 but were delayed after CFTC flagged the product as novel or complex, extending the review to a Nov 9 completion date, with CME marking the initial listing date as to be announced. Meanwhile ICE and Ornn began publishing Ornn Compute Index reference data, Kalshi already offers GPU compute price prediction contracts and forward curves, and Architect and Nodal Exchange are moving on similar products. Interviews with Chinese compute rental firms, cloud vendors, model companies and AIDC park operators found no mature public compute price index domestically, so firms rely on long-term contracts, prepayments and reserved capacity, while Nanhua Futures unit Henghua International signed a memorandum with Silicon Data.

   36氪 人工智能 · 🔥 0
3. Oct 11
   Cheaper AI tokens are driving more demand — a textbook Jevons paradox

   The Decoder reports that a16z calls the current AI market a "textbook Jevons paradox": data from Ornn, Silicon Data and Bloomberg (as of August 2026) shows token prices keep falling while H100 GPU rental prices hold steady or even climb. Cheaper tokens unlock agents, automation and new applications, so volume grows faster than per-unit costs fall, though the article notes it is unclear how much demand comes from humans versus agentic systems burning tokens at a staggering rate, and that compute demand could be artificially inflated. The whole chain rests on one assumption — AI usage grows fast enough to offset falling token prices; if demand flattens, chip makers, memory suppliers, energy providers and cloud companies take a hit, and US stocks already dropped on reports that OpenAI's annualized revenue might be lower than previously reported.

   The Decoder · 🔥 0

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