The article examines how much of a decentralized AI compute network's hardware actually produces tokens that users requested, noting that consensus overhead, redundant verification, and idle capacity consume GPU-hours that never reach an end user. It states that a dashboard's per-network throughput column now exposes this inefficiency. Five networks are said to attack the problem from genuinely different directions, each carrying a limitation worth knowing before going deeper.
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