Account: One Codex Pro 20x account, using only GPT‑5.6 Sol Standard.
Measurement: The author used a CLI they wrote with Codex to count local tokens and cross-checked the results against a corrected version of ccusage; the two results matched.
Measurement windows: Measurements were recorded across two independent allowance cycles: one banked reset and one global reset about three hours later.
The article measures subscription allowance and its Standard API equivalent, not model quality on a fixed coding task.
It records the usage percentage displayed by OpenAI, credits, local token measurements, and the dollar value converted at the official rates.
The author notes that older versions of ccusage overestimated usage by about 20% and that the corrected version must be used.
After the banked reset: 6,643 credits (13%).
After the global reset: 35,915 credits (67%).
Combined across both windows: 42,559 credits, equivalent to approximately $1,702 in Standard API usage.
Extrapolating from the percentages, a weekly Pro 20x window contains approximately 52,000–56,000 credits, with a midpoint of 53,600 credits, equivalent to about $2,144 in Standard API usage.
The observed conversion was approximately 25 Codex credits = $1 of Standard API usage; the author says this matches the official rates and the percentage dashboard within rounding error.
Based on this, the author estimates approximately $8,300–$8,900 across four weekly windows, or approximately $9,000–$9,700 in an average month.
This is a subscription-allowance record backed by local measurement and cross-checking, making it useful for estimating a Sol Standard spending budget. It does not say anything about Sol's task success rate, nor can one account and two resets be generalized to the allowance available to all Pro 20x users.
It covers one account and a short observation period, and includes banked and global resets, so differences by account, time period, or reset policy cannot be ruled out.
There is no fixed task set, input prompt, toolchain, cache-hit rate, or per-task quality result.
Converting credits to API dollars depends on the product's internal measurement rules; the 25:1 ratio is observed only in this report and is not an independently verified official commitment.
The article's comment section contains different allowance experiences, further indicating that usage is affected by the task and harness.
Use one clearly defined subscription tier and one model tier, and record the credits/percentage at the start of the window.
Use a CLI to record input, output, and cached tokens, and independently verify them with the current corrected version of ccusage.
Record regular, banked, and global resets separately; do not combine multiple windows into a single experiment.
Convert to the API equivalent using the official rates for that day, while preserving the raw measurements and conversion formula.
Repeat across multiple accounts and weekly windows, reporting the median, range, and task types.
The main post makes public the credits, usage percentages, totals, conversion values, and estimated ranges for both windows.
The author publicly explains the cross-measurement tools and the overestimation issue in older versions of ccusage, making this report more verifiable than a simple impression that the “allowance ran out very quickly.”
Suitable as a starting point for subscription budgeting, allowance monitoring, and validating measurement tools.
Not suitable for comparing Sol's intelligence, code quality, or long-horizon Agent success rate with other models.
If the product's measurement, rates, or plan change later, the old report should be collected again.
The author summarizes their method as “controlled test using only one Pro 20x account”.
GPT-5.6 Sol
