GPU prices are climbing again, and the latest TechSpot numbers show how bad things have become. Average GPU prices rose 15% in one month, with Nvidia cards up around 19% and AMD cards about 11%. Some models are now far above official prices: - RTX 5060: around $450, 51% above MSRP - RTX 5060 Ti 16GB: around $730, 70% above MSRP - RTX 5090: nearly $4,900, 145% above MSRP

GPU fleet unit economics. TLDR: Tough to be bearish on $NBIS or $CRWV right now. Some maths, but it's important to understand. Using $NBIS 1-3yr contract economics: - $20-25M ACV per MW at a payback of 1 year 10 months. - Take $22.5M midpoint ACV/MW at a ~55% cash margin ( $NBIS core AI cloud runs ~50%, $CRWV 59%) and you get ~$12.4M/MW of annual cash flow. (Payback runs against cash flow, not revenue) - 1.83 years of that implies "all-in" capex of ~$20-23M per MW (GPUs included). - Which ties to Nebius' $20-25B capex guide for 2026 against ~1GW. - Over a 4-5 year life that's roughly $50-62M/MW of cumulative cash flow against ~$22M of capex. - NPV is +$20-25M per MW even discounting at 12-15% and IRR near 50%. Then years 1-2 of DCF nearly cover the entire capex on their own. Meaning that the GPU could go to $0 residual after year 2 and the deal basically breaks even. That is insane. So really, the bear case doesn't need slow decay to be wrong. Rather, it needs the contracted years themselves to fail. And those years are effectively walled off rn. - Around 70% of $NBIS deals carry prepayments covering 50-60% of the capex, on take/pay terms. - $CRWV's $104B backlog is take/pay with ~21% of it recognized more than four years out. As we now know, $CRWV signed an A100 contract running into 2029 (a SKU introduced in 2020) "at or above where it was years ago", and CEO told CNBC a batch of H100s coming off an expired contract was re-booked immediately at 95% of the original rate. $NVDA's CFO also said that A100s shipped 6 years ago are still running at full utilization. And $NVDA is now willing to underwrite residual value itself, up to 25% per project in the new financing platforms. I don't think they'd be willing to backstop if they expect GPUs to be worthless in around 3 years or so. For the neoclouds themselves though, depreciation is the biggest cost driver e.g. Nebius D&A was larger than their adj EBITDA last Q. If economic life actually extends to a new base case scenario of 5-6 years rather than the old 3-4 years... Earnings power re-rates higher across $CRWV, $NBIS and even the hyperscalers as ultimate beneficiaries.

GPU compute now has an index, a forward curve, and CME futures coming in H2. @carmenli built that market — and has watched crypto trade the same AI thesis through H100 perps and pre-IPO bets. She tells @‌Steven_Ehrlich what holds up and what breaks. Streaming today at 12pm ET 👇 Join us on: x -

GPU-Backed Debt and the case for the End of SaaS Credit Shoal Signal Ep. 7 with @0xZergs, co-founder/CEO of @USDai_Official, hosted by @zaddycoin AI compute is being built faster than the financial system can finance it. Chips refresh every 24 months, and the debt that funds houses and planes needs decades of data and years to structure. David walks through why he thinks most of DeFi is money lending against money, and not real credit. 0:00 From art financing to GPU credit 2:18 DeFi is money market, not capital 3:13 Why CoreWeave bonds are not ABS 5:25 Convertible debt and the miner playbook 6:31 What securitization actually needs 9:03 Hyperscalers versus the Neo cloud tail 9:37 The depth perpetual idea 12:30 Underwriting eight chips, not companies 17:14 Why most RWAs are "toxic waste" 21:11 SaaS credit is dead 23:03 GPU loans as a super sector 26:37 Inside the Nvidia financing gap 30:20 Why only Nvidia chips 33:12 Compute as the next stablecoin 35:31 PYUSD, USDAI, and lowering the rate 38:34 Insurance with Barker and Munich Re 40:13 Internet capital markets versus margin 42:25 Where on-chain credit actually wins Youtube:

GPU shortage is worse than ever. H100s cost more today than they did 3 years ago, and you cannot get them on-demand. The big AI labs have locked up most of the supply for years. I’m worried university researchers and individual developers simply won’t be able to get GPUs.

GPU shortages. Rising memory costs. Cloud outages. Different failures, same choke point: Compute. It’s becoming the defining resource of this century, yet access today is scarce, expensive, and controlled by a few. ComputeFi changes that 👇

Nvidia GPU Debt Backstop Unleashes the AI Project Trinity: Capital, Offtake and Datacenters Over 7T AI debt by 2029, There can be no Neoouds without the Trinity. Nvidia's Backstop Economics Explained. AI Debt Needs Quantified. Nvidia's Objective is to Broaden Compute Access