Hua Er Jie Jian Wen·2025-10-27 02:13Core Insights - Google Cloud has secured a significant deal with AI unicorn Anthropic, marking a major victory in the competitive AI landscape [1] - The partnership is expected to generate substantial revenue growth for Google Cloud and exert pressure on its main competitor, Amazon [1] Group 1: Partnership Details - Anthropic has announced an expansion of its collaboration with Google Cloud, gaining access to up to 1 million Google TPU chips for training and servicing its next-generation Claude model [1] - The total value of this deal is estimated to be in the "hundreds of billions," with projections suggesting a contract duration of approximately 6 years and a total value between $50 billion and $80 billion [1][2] - Anthropic anticipates having over 1 gigawatt (GW) of online computing power by 2026, driven by the cost-effectiveness and efficiency of Google TPU [1] Group 2: Revenue Impact on Google Cloud - This partnership is seen as a validation of Google’s AI cloud strategy, with projections indicating it could accelerate revenue growth for Google Cloud (GCP) by 100 to 900 basis points in 2026 [2] - By 2027, the collaboration is expected to contribute approximately $9 billion to $13 billion in stable annual revenue for Google Cloud [2] Group 3: Competitive Landscape - Amazon Web Services (AWS) has historically been Anthropic's primary infrastructure partner, but Google Cloud's involvement challenges AWS's exclusive position [3] - A comparison of computing power shows AWS currently holds about two-thirds of the market share, but it failed to secure this critical incremental order, raising questions about its technological competitiveness and pricing strategies [4] Group 4: Technical Differentiation - The computing power provided by Google Cloud will primarily focus on "inference" rather than "training," as AWS remains Anthropic's main training partner [5] - The upcoming Google TPU v7 (codename Ironwood) is designed for efficient inference tasks, allowing Google to establish a strong competitive edge in specific segments of the AI workflow [5]