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hot_img SemiAnalysis: SpaceX may complete a 10GW data center by 2027, with expected inference revenue reaching $300 billion

Research institution SemiAnalysis released an analysis stating that SpaceX is expected to build approximately 10GW of AI data center capacity by the end of 2027. If 50% of this is used for inference services, with annual revenue exceeding $10 billion per GW, the annualized revenue could reach $300 billion. SpaceX CEO Elon Musk stated in the first earnings report that a "conservative estimate" suggests an additional 6-8GW will be added in 2027, with the actual figure possibly exceeding 10GW.SemiAnalysis's inference simulator shows that when running on the GB300 cluster at current startup cloud prices (about $3/GPU hour), leading model companies like OpenAI and Anthropic could generate annual inference revenue exceeding $10 billion per GW, with annual costs around $12 billion. Microsoft, with full access to OpenAI models and without bearing training costs, can also capture revenue of the same scale. The analysis points out that Microsoft has signed contracts for 10GW of data centers (total value exceeding $300 billion) since 2026, with a 90-day cancellation clause, significantly reducing signing risks.Regarding SpaceX's construction progress, SemiAnalysis believes Musk will significantly shorten the construction cycle by using onsite gas power generation, bypassing large power transformers, parallel construction, and shortening the debugging process. The Southaven plant in Tennessee expanded from 27 turbines (approximately 495MW) in February to 69 turbines (1.7GW) in July, and the "MiniHard" project can be completed in about 5 months with 450-500MW. However, the 10GW target still faces multiple challenges such as land approvals, gas supply, and equipment delivery. This analysis is based on model simulations, and actual implementation still carries uncertainties.

hot_img SemiAnalysis: Gemini has exited the frontier competition, and GCP is accelerating the sale of TPUs to third parties for profit

The research organization SemiAnalysis released an analysis indicating that Google DeepMind is no longer among the leading AI laboratories. A week prior, DeepMind co-founder Demis Hassabis stepped back from daily operations, and key members such as Google Chief Scientist Jeff Dean and Gemini co-lead Oriol Vinyals left to establish a new lab called Discovery Loop. The analysis suggests that the long-term struggle within Google over computing power allocation between Gemini and GCP has concluded with GCP emerging victorious.SemiAnalysis stated that Gemini 3.5 Pro has been canceled, and Gemini 3.6 Flash's performance is inferior to that of leading Chinese open-source models and Grok 4.5. Currently, Gemini has fallen to the 8th or 9th position in the large model rankings. Meanwhile, GCP is selling a large number of TPUs to competitors like Anthropic, having secured long-term leasing and sales contracts for hundreds of thousands of TPUs over the past nine months. The Tokenomics model estimates that Gemini's own ARR is about $12 billion, while GCP's third-party AI cloud service revenue is expected to exceed $73 billion by the end of 2027, with TPU system sales contributing an additional over $120 billion. GCP's latest quarterly growth rate is 82%, and it is expected to accelerate to over 100% by 2027 due to TPU system sales, contributing approximately $3 to Google's earnings per share.

SemiAnalysis: Changxin Storage has become the fourth largest DRAM manufacturer in the world, and will not break the super cycle of storage shortages in the short term

The semiconductor research institution SemiAnalysis has released a latest analysis indicating that Changxin Memory Technologies (CXMT) has clearly become the world's fourth largest DRAM manufacturer. Although its production capacity and cash flow are continuously growing, the institution believes that Changxin Memory still faces multiple challenges in equipment, technology, and market, and will not end the current storage "super cycle" in the short term.In terms of specific challenges, export controls on advanced semiconductor manufacturing equipment (such as EUV, advanced etching, and TSV tools) severely restrict Changxin's expansion into more advanced processes and high bandwidth memory (HBM) fields; although domestic equipment (such as Zhongwei Company, Northern Huachuang, etc.) has alleviated some pressure, it cannot fully resolve the integration and yield bottlenecks across multiple process links, resulting in its technology still lagging behind leading manufacturers by several generations. Additionally, Changxin's market share is currently still highly concentrated in the Chinese domestic market, with global expansion limited by geopolitical factors and customers' willingness to diversify their supply chains.In response to market concerns that Changxin might "impact the global market with cheap chips," SemiAnalysis clarified that there is currently a severe structural shortage in the DRAM market, and the increase in Changxin's production capacity may even struggle to fully meet domestic demand in China. In fact, the prices of Chinese memory chips are also soaring significantly, in line with the global upward trend, and Changxin is similarly a beneficiary of the shortage premium. Therefore, Changxin Memory should be viewed as a long-term structural competitive force, and in the current context of accelerated AI demand and constrained supply, it cannot shake the fundamental super cycle dominated by leading manufacturers in the short term.
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