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Recorded Election Day morning, before any results: SemiAnalysis’s model has about 62 GW of US datacenter additions in 2028, most not yet under construction and sitting in states electing a governor. Texas alone is close to 30%. Jordan Nanos (@JordanNanos) sits down with Maya Barkin (@mayabarkin), Wayne Ma (@waynema) and Jeremie Eliahou Ontiveros (@JeremieEO) on why 2027 is largely locked in, why the backlash crosses party lines, and how developers can win over their neighbors. Since recording: the AP called Texas for Gina Hinojosa, who would pause datacenter permitting, and Georgia for Keisha Lance Bottoms, and Democrats took a 3-2 majority on Georgia’s Public Service Commission, which sets power rates. (As of Nov 4, 2:35 PM ET.) Read the article: https://newsletter.semianalysis.com/p/the-datacenter-backlash-goes-bipartisan 0:00 Intro 0:54 The 2028 Buildout 5:32 Pause vs. Conditions 10:03 Bipartisan Backlash 14:37 Grid Risk 16:30 Tax Incentives 19:51 Texas 24:34 Risks to 2027 30:23 Georgia 32:31 Federal Outlook 35:20 Winning Over Neighbors 42:04 What We're Watching

SemiAnalysis just launched GDPx, a benchmark built with 14 specialized data partners across 11 domains where frontier intelligence earns the highest returns. Even the best model scores just 12%. Jordan Nanos (@JordanNanos) sits down with Max Kan (@maxkan) and Andrew Megalaa (@AndrewMegalaa) to explain why most popular benchmarks are broken, the difference between difficult and unfair tasks, how a real private equity deal room became a finance environment, why binary grading still matters, and what the leaderboard says about Opus 5.5, GPT-6 Astra and Gemini 4 Carbon. Explore GDPx: https://gdpx.semianalysis.com Read the article: https://newsletter.semianalysis.com/p/gdpx-measuring-frontier-model-capabilities Want your model evaluated or to partner on a future version? [email protected] 0:00 Cold Open 0:10 Launch Week Chaos 4:02 Broken Benchmarks 5:15 Difficult vs. Unfair 7:33 Building GDPx 9:25 Frontier Domains 11:02 The 11 Domains 14:12 Domain Experts 15:00 Models vs. Experts 19:36 Model Behavior 20:44 The Leaderboard 22:33 Cyber and Safety 24:32 Frontier vs. Day-to-Day 27:13 The Finance Task 31:27 Binary vs. Partial Grading 36:48 AI and Jobs 42:43 Quick Takes 43:44 Google's Comeback 47:25 Public vs. Private Tasks 49:52 What's Next

Anthropic filed its S-1: revenue per dollar of compute is up 5.2x since Q1 2025, a customer who spent $1 last year now spends $9, and incremental gross margins are running near 90%. Jordan Nanos (@JordanNanos), Doug O'Laughlin (@fabknowledge), Jeremie Eliahou Ontiveros (@JeremieEO) and Joey Brookhart (@SaasquatchC) break down profitability, the half trillion in compute commitments, customer concentration, the 2027 compute roadmap, and whether OpenAI can keep up. 0:00 Cold Open 0:53 Profitability 2:10 The Datacenter View 4:14 Compute Commitments 6:28 Incremental Margins 8:19 Customer Concentration 12:00 Top Customers 16:53 New Funding 18:54 Underpromise, Overdeliver 20:25 Elon and Neoclouds 25:14 Compute Efficiency 29:40 Can Anyone Catch Up? 33:26 Surprises and Runway 37:47 Market Reaction 39:02 Holiday Usage 42:56 Is OpenAI Cooked? 48:44 Government Revenue 50:45 Wrap-Up

Every hybrid bonder on the market today brings the die to the wafer. ASML's patents bring the wafer to the die.Sherry Zhang and Howie join Jordan Nanos (@jordananos) to dig into the patents behind ASML's die-to-wafer hybrid bonder, why a track-based design could beat Besi on alignment and particle control, and why HBM won't adopt die-to-wafer hybrid bonding before 2029. The team also looks at how China is using hybrid bonding to keep scaling past its lithography limits, and what larger photomasks mean for High-NA EUV.Chapters:0:00 The Patent Tip-Off1:53 Hybrid Bonding 1014:06 Die-to-Wafer vs Wafer-to-Wafer5:43 Back End vs Front End8:05 Why HBM Waits Until 202913:45 Everything Comes to the Die18:26 Alignment and Cleanliness22:48 Bonding Instead of Shrinking25:49 China's Toolmakers Step Up28:25 Bigger Masks for High-NA33:29 Two Tool Stacks?Read the full article: ASML Is Building a Hybrid Bonding Tool!https://newsletter.semianalysis.com/p/asml-is-building-a-hybrid-bonding

Brad Gerstner put our 43 gigawatt forecast for 2027 on All-In, then again in his BG2 sit-down with Jensen, and called it too aggressive. The consensus counter sits near 25 GW, built on moratorium headlines and grid connection fears. Jordan Nanos (@JordanNanos) sits down with Jeremie Ontiveros (@JeremieEO) and Reyk Knuhtsen (@robotknower), who have been tracking the same capacity curve since March 2024, and it has barely moved across every model revision. So they aren't cutting it. They're raising it. Read the article: https://newsletter.semianalysis.com/p/datacenters-2027-the-year-of-acceleration 0:00 Cold Open 1:17 The 2027 Forecast Debate 2:21 Model Track Record 5:27 Where the Pushback Comes From 8:16 Delays and Haircuts 12:31 The Top 40 Sites 15:23 Leading Indicators 20:40 Modular Builds 25:41 Chips vs Datacenters 27:53 Responding to Brad Gerstner

GLM 5.3 only attends to the tokens that matter. It still has to keep every one of them. Kimbo Chen (@kimbochen) and Wenyao Gao (@gao_wenyao) join Jordan Nanos (@JordanNanos) to dig into AMD catching NVIDIA on InferenceX, how post-training alone pushed an open-weight model within reach of Mythos, and whether Z.ai quietly tuned it for Chinese chips. The team also looks at how GLM 5.3 became a fallback when Claude and GPT refuse security work. Chapters: 0:00 Cold Open 0:37 Sparse Attention 101 4:46 HiCache and HiSparse 10:13 AMD Catches NVIDIA 12:54 Capacity vs Bandwidth 18:44 The Frankenstein Flash 20:09 Mythos-Class From China? 22:52 Post-Training Pipeline 32:32 Chinese Chips, Day One 39:54 GLM 5.4 and Beyond Read the full article: How GLM 5.3 Sparse Attention Affects HBM Memory Usage https://newsletter.semianalysis.com/p/sparse-savings-persistent-demand-inside-glm53

H100 rental prices went up, on a GPU that should be sliding down its depreciation curve. That curve is what lenders underwrite. Daniel Nishball (@dnishball) kicks off our new Compute Capital Markets group by following the money through Nvidia's $497B backstops, ClusterMAX as a credit signal, and whether each token is profitable. Jordan Nanos (@JordanNanos) brings the rental data. AI debt is about to pass auto loans. 0:00 Opening 1:48 Nvidia's Backstop Universe 6:22 The $11T Funding Wall 17:25 Balance Sheet as a Service 26:27 ClusterMAX as Credit Risk 31:51 Why H100 Prices Rose 43:09 Token Profitability 58:05 You Can't Go Back 1:07:25 AI Debt vs Auto Loans 1:11:14 Inside Nvidia's Backstops

Pay Anthropic $200 a month and you can pull $12,000 of Opus 5.5 tokens at API pricing. Max Kan (@maxkan) and Andrew Megalaa bought every plan, OpenAI, Meta, xAI, MiniMax, Moonshot, Z.ai, Cursor, and measured every token type to find the ceiling. The catch isn't subsidy. Anthropic still books 50 to 60% gross margins on these plans, which means the API itself is the price gouge. 0:00 Cold Open 1:03 Subsidies and Credits 5:23 Token Types and Cache 14:08 Model Value Charts 20:51 Test Methodology 26:54 Other Plans 31:26 Utilization and Limits 36:24 Token Efficiency 41:24 Open Models 44:22 Cyber and Capture Read More: https://newsletter.semianalysis.com/p/anthropic-subscriptions-offer-5x

Jordan (@JordanNanos) and Abhilash (@AbhilashJain17) discuss the clients SemiAnalysis consulting serves, custom projects like the inference simulator, how client work turns into research products, neocloud due diligence, and why SLAs decide who gets funded. They also discuss Feynman specs, de-specced memory, and a 20-trillion-parameter OpenAI model. 0:00 Intro and Overview 2:27 Client Types 5:24 Custom Projects 9:47 Strategy Work 12:27 Consulting to Products 14:33 Neocloud Due Diligence 18:40 SLAs and Insurance 22:32 Risk Assessments 26:45 Build vs Buy 29:19 Favorites and Outlook

The InferenceX team is back after two months. Jordan Nanos (@JordanNanos) is joined by Cam Quilici (@noslawextratost), Bryan Shan, and Alec Ibarra to discuss Engram and DRAM offloading, the AgentX benchmark and its profit calculator, TPU v7 on InferenceX, Vera Rubin vs Blackwell, fast tokens, and TileRT on NVIDIA GPUs. 0:00 Intro 0:31 Engrams 12:27 AgentX Benchmark 16:36 Profit Calculator 23:40 TPU v7 32:03 Vera Rubin 40:49 Fast Tokens 49:33 TileRT 54:00 Chip Startups 1:01:31 Wrap Up

ClusterMAX 3.0 is here. Sam Harshe (@sharshe02) and Pratt Bhatt (@PrathmeshBhat19) join Jordan Nanos (@jordannanos) after months of testing 77 GPU clouds. Some moved up, some moved down. Health checks, cache hit rates, NCCL recipes, agentic coding on clusters, a Linux kernel bug, neocloud security, SLAs and financing, NVIDIA's backstops, five-year-old H100s, and hosted RL training. Read the full ClusterMAX 3.0 report: https://newsletter.semianalysis.com/p/clustermax-30-the-industry-standardClusterMAX inquiries: [email protected] 0:00 Cold Open 1:32 The Rankings 6:58 Health Checks 13:26 Endpoint Cache Misses 16:40 Networking and NCCL 22:52 Vibe-Coded Infra 31:27 Bug Hunting 38:36 Security 45:43 Financing Neoclouds 56:33 Hosted Training and RL

More than 300 towns, cities, and counties have voted to pause data centers in the past 18 months. Maya Barkin (@mayabarkin) and Reyk Knühtsen (@robotknower) from the SemiAnalysis Data Center, Energy, and Industrials team join Jordan Nanos (@jordannanos) to explain what a moratorium actually is, how they mapped every one of them against the US project pipeline, and why only three projects are being delayed. Plus: the SpaceX de-annexation in Brownsville, New York vs Texas, why politicians love a moratorium, and the surprising amount of alpha in anti-data center Facebook groups. Jeremie Eliahou Ontiveros (@JeremieEO) drops in from Bangkok. Read More: https://newsletter.semianalysis.com/p/everyone-says-datacenter-moratoriums 0:00 Intro 0:36 What Is a Moratorium 4:34 300 Moratoriums, 3 Projects 10:18 Behind the Meter Wins 14:04 Eight Conditions to Delay 17:06 The SpaceX De-Annexation 20:03 Cheap Political Signaling 32:03 New York vs Texas 41:14 City Council Alpha 46:32 Advice for Developers

Emergency episode. Doug O'Laughlin (@Fabknowledge) , Joey Brookhart (@SaasquatchC), and Max Kan (@maxkan) join Jordan (@JordanNanos) to talk through Dario's "We Must Pace the Frontier" blog and the responses from Sam Altman and David Sacks. Does pacing actually mean less compute, or a lot more? Plus the Hugging Face incident, Moonshot serving Claude, and the security behaviour that keeps them up at night. 0:00 Cold Open 2:50 Glorified Neoclouds 8:21 Pacing the Frontier 12:53 Safety Eats Compute 20:38 Hugging Face Lessons 30:52 Moonshot Serving Claude 36:37 The Coxson Resignation 38:27 Two-Year Predictions 49:19 Regulation Under Trump 57:21 Hotter or Cooler

NVIDIA previewed Rubin Ultra at 1TB of HBM per package. The part that ships will carry 192GB. Myron Xie and Jordan Nanos get into how the design fell that far, why the reason is supply and not performance, and why shipping less memory per chip might be the right call anyway. For the first time in recent memory, NVIDIA's next flagship will have less capacity than the one it replaces. Read More: https://newsletter.semianalysis.com/p/long-live-the-short-king-why-4-hi

Traditional data center builds ran 18 to 24 months, sometimes past three years. Modular construction cuts that to 12. Jordan Nanos (@JordanNanos) sits down with Eric Wen, Nigel Chiang, and Nico Bontigui to map what modular actually means, from MEP heavy skids to full containerized builds. They break down why the bottleneck moved from construction time to labor, why welders and electricians are the real constraint in Abilene, and how time to power translates directly into tokens at 40 to 100 million dollars per megawatt. Subscribe for weekly SemiAnalysis coverage on data center construction, prefabrication, and AI infrastructure. 0:00 Cold Open 1:09 What Is Modular 4:03 Why Go Modular 5:55 Time to Power Math 9:04 Labor Wage Data 13:51 Two Kinds of Bottlenecks 18:24 Site, Shell, System 22:31 Who Owns the Risk 26:59 Trucks and Insurance 30:53 Who Supplies the Modules 35:50 Commissioning Reality 41:39 Vendor Map and Wrap Read More: The Wild Wild West Of LEGO Datacenters: https://newsletter.semianalysis.com/p/the-wild-wild-west-of-lego-datacenters