Banyan Ventures on X: "There’s a major misconception in the AI infrastructure world right now: that GPUs follow a fixed 4–6 year depreciation curve. They don’t. Not even close. Aravolta highlights what most lenders, operators, and investors are still missing: Two identical GPUs can age at" / X

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To view keyboard shortcuts, press question mark View keyboard shortcuts Home Explore Notifications Chat Grok Communities Premium Profile More Post kristie! @kristiehuang Post See new posts Conversation Aravolta reposted Banyan Ventures @Banyan_Ventures There’s a major misconception in the AI infrastructure world right now: that GPUs follow a fixed 4–6 year depreciation curve. They don’t. Not even close. Aravolta highlights what most lenders, operators, and investors are still missing: Two identical GPUs can age at completely different rates depending on the workload, utilization patterns, and thermal behavior. 1. Workload determines lifespan far more than hardware does. A GPU running steady 60–70% inference may last 5+ years economically. A GPU hammered with daily 95–100% training spikes may lose economic life in under 3 years. Same chip. Same SKU. Completely different depreciation path. 2. Thermals are destiny. Every 10°C increase can cut component life roughly in half. Many

Banyan Ventures @Banyan_Ventures There’s a major misconception in the AI infrastructure world right now: that GPUs follow a fixed 4–6 year depreciation curve. They don’t. Not even close. Aravolta highlights what most lenders, operators, and investors are still missing: Two identical GPUs can age at completely different rates depending on the workload, utilization patterns, and thermal behavior. 1. Workload determines lifespan far more than hardware does. A GPU running steady 60–70% inference may last 5+ years economically. A GPU hammered with daily 95–100% training spikes may lose economic lif

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