Based on this quote from the GPT6 announcement: “Valued at API prices, daily token usage has exceeded $600 for the median researcher and $7,000 for researchers at the 90th percentile”.
Estimated slop ratioWhere 0% is full human with absolutely zero AI involvement and 100% is the cause of great dismay.: 80%
September 22, 2026
An estimate for 1,125 researchers, assuming 25% of 4,500 employees are researchers. This values token usage at API prices; it does not estimate OpenAI’s internal costs.
1Assumptions #
OpenAI reports daily token usage above $600 for the median researcher and above $7,000 at the 90th percentile, valued at API prices.[1] The Financial Times reported about 4,500 employees in March 2026, as relayed by Reuters.[2]
Assume 25% are researchers, and their daily usage follows a lognormal distribution. Treat $600 and $7,000 as exact quantiles for this calculation. Neither the 25% share nor the distribution is reported by OpenAI.
2Calculation #
Let X be a researcher’s daily usage value, measured in USD. For a lognormal distribution:[3] Here, Φ⁻¹ is the inverse standard normal cumulative distribution; Φ⁻¹(0.90) ≈ 1.281552.
The mean—not the median—is the quantity to multiply by headcount:
The estimate excludes non-researchers’ usage and training compute. It is an expected daily value under the assumptions, not a measured company total.
3Usage and concentration #
Limits. The source says “exceeded,” not “equal to.” Its two thresholds do not establish the mean or the upper tail, so $4.24M is not a proven lower bound. The March headcount and later usage observations are from different dates. All three charts are calculations, not employee data.
References #
OpenAI. Research acceleration: The view inside OpenAI. September 6, 2026, §1. Median observation: mid-August. Repeated in Introducing GPT-6 Sol and Luna, September 22, 2026.
Reuters. OpenAI to nearly double workforce to 8,000 by end-2026, FT reports. March 21, 2026. Reported headcount: 4,500; 8,000 was a hiring target. Reuters did not independently verify the FT report.
NIST/SEMATECH. e-Handbook of Statistical Methods, §1.3.6.6.9: Lognormal Distribution. Distribution, quantiles, and mean. Parameters and results calculated here.