Ep. 038 - GLM 5.3 on AMD, NVIDIA, and Chinese Chips From Day One (InferenceX) | Kimbo Chen, Wenyao Gao, Jordan Nanos
SemiAnalysis WeeklyShow Notes
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
More from SemiAnalysis Weekly
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.
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.
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.
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.