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Analysis

TSLA FSD — 315M Miles/Day · Up From 28.8M Just Months Ago

Published · Updated · By Investus editorial desk (SUNRYU Partners)

Per Sawyer Merritt citing Tesla's Vehicle Safety Report, FSD (Supervised) fleet now drives 315M miles/day — up from 28.8M months ago and 14.4M earlier this year (1,000 miles every 2.3s). Cumulative 12.6B miles total, 4.85B city miles. Training-data pipeline scaling exponentially.

TSLA FSD — 315M Miles/Day · Up From 28.8M Just Months Ago

Key Numbers

Big update to Tesla's Vehicle Safety Report (via Sawyer Merritt): FSD (Supervised) fleet averages 315M miles/day. Months ago it was 28.8M/day; earlier this year 14.4M/day. That's roughly 1,000 miles accumulated every 2.3 seconds.

- Cumulative total: 12,609,051,466 miles (12.6B+)

- City miles: 4,855,171,132 (4.85B+)

Why It Matters

Autonomy performance depends strongly on training-data volume and quality. 315M miles/day reflects (1) 1.48M+ active paid FSD subscribers being actually used, (2) exponential expansion in the training pipeline feeding V15, and (3) real robotaxi operations in specific cities pushing up the city-mile share.

Tie-in With Musk's Cybercab Explanation

Joe Hansen's compilation of Musk's remarks today explains why Cybercab can't instantly scale despite this massive miles surge — a new chassis needs its own data, and existing-fleet miles don't auto-transfer. Data acquisition is exponential; new-platform commercialization is throttled by validation.

Watch Next

(1) When this miles surge reflects into V15 training speed, (2) quantitative improvements in the safety report (accidents, disengagements), (3) when city-mile share expands past 40% of total.

Sources & further reading

See the body and ticker IR links for sources on this note.

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Disclaimer

This article is editorial research for informational purposes only. It is not investment advice, a recommendation, or a solicitation to buy or sell any security, and does not guarantee any return. Markets carry risk of loss. Verify figures against the primary sources before making decisions.

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