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OpenAI · REASONING EFFORT GUIDE

GPT-6 Sol
How much thinking?

Compare Low vs Medium vs High vs Extra high vs Max where tested. Find the effort setting that fits your task, and see how much extra reasoning changes the result.

SAME MODEL. DIFFERENT THINKING.

Choose a thinking level for GPT-6 Sol

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Hex DataBench v1.1

Published blended DataBench score, on a 0–100 scale. Judge-based analytical task performance; not a general intelligence or guaranteed success rate.

Analytics in the Hex agent harness · Leaderboard updated: 2026-09-22 · Reviewed 2026-10-15Check the source ↗
SUGGESTED SETTING TO TESTExtra high

Lowest measured cost within 1.0 points of the best tested analytics score.

61.3 / 100 · $0.5817 / source task
Exact best1.0 pts10 pts

Set 0 for the highest score. Increase the gap to explore cheaper or lighter options.

THE EFFORT CURVE

Does more thinking help?

● Near-best pickOrange = score decreased

025507510050.3Low51.3Medium54.7High61.3Xhigh57.0Max
025507510050.3Low51.3Medium54.7High61.3Xhigh57.0Max

Scores out of 100 · Full 0–100 scale · tap a point to select mode B. Cyan band: within 1.0 points of the best tested score.

WHAT YOU SPEND

Cost of more effort

Measured average USD per benchmark task.

Low$0.1748
Medium$0.2708
High$0.3874
Extra highNear-best pick$0.5817
Max$0.9845

Measured in this study with its particular tools and setup. Your task mix, tools, caching and endpoint can change the result.

Score difference · B minus A-4.3 pts

Noticeable gap · B scored lower

Measured cost · B / A1.69×

Same benchmark workload

Median duration · B / A1.89×

Measured with the study’s testing setup

We describe gaps under 1 point as small, 1–under 5 as noticeable, and 5 or more as large. These are reading aids, not proof that a difference would hold up in repeated tests. Equal scores can still hide different mistakes.

WHERE MORE SCORED LOWER

When more thinking scored lower

Extra high → Max-4.3 pts61.3 → 57.0 on analytics score

These drops can reflect the tasks, variation between runs, testing tools or errors. A lower score alone does not prove the model was “overthinking.”
EVERY TESTED MODE

Results for each tested setting

5 modes · untested settings are left blank

Low

Tested setting
50.3 / 100

-11.0 pts vs Extra high

$0.1748 / source task

98 s median duration

Medium

Tested setting
51.3 / 100

-10.0 pts vs Extra high

$0.2708 / source task

146 s median duration

High

Tested setting
54.7 / 100

-6.7 pts vs Extra high

$0.3874 / source task

238 s median duration

Extra high

Suggested setting
61.3 / 100

0.0 pts vs Extra high

$0.5817 / source task

327 s median duration

Max

A better tradeoff is available
57.0 / 100

-4.3 pts vs Extra high

$0.9845 / source task

618 s median duration

Full benchmark table & exact configuration IDs

Swipe inside the table for all measures. Figures from different study selections are not directly comparable.

GPT-6 Sol · Hex DataBench v1.1 · Analytics in the Hex agent harness
EffortAnalytics scoreCost / taskMedian secondsOutput tokensExact source ID
Low50.3$0.174897.6—GPT-6 Sol · Low
Medium51.3$0.2708146.2—GPT-6 Sol · Medium
High54.7$0.3874238.0—GPT-6 Sol · High
Extra high61.3$0.5817326.7—GPT-6 Sol · XHigh
Max57.0$0.9845617.5—GPT-6 Sol · Max
SCALE THE OBSERVED COST

Effort cost difference calculator

What would A versus B cost if you repeated this benchmark’s average workload?

A · Extra high$581.65
B · Max$984.49
Difference$402.83more with B

A source-workload scenario using average measured USD costs. Source prices, caching and tools are already reflected in those observed costs. Your agent’s costs may differ.

YOUR WORKLOAD

Reasoning-token cost calculator

Estimate the extra bill from thinking tokens. The starting token counts are editable examples, not measurements of GPT-6 Sol. Rates start from the current model snapshot.

A · Extra high$40estimated monthly cost
B · Max$80estimated monthly cost

Mode B costs $40 more per month with these assumptions.

This estimate uses the token counts and prices you enter. Excludes retries, tools, caching, long-context premiums, hosting and taxes. Includes thinking in output billing; do not also include it in “visible output.” Check endpoint limits separately. Changing mode does not automatically predict tokens or quality.

READ ACROSS THE EVIDENCE

GPT-6 Sol effort benchmarks at a glance

Each card compares settings tested together in one study. Scores from different benchmarks or question sets measure different work and are not averaged together.

Leaderboard updated · 2026-09-22

Analytics · DataBench v1.1

Published blended DataBench score, on a 0–100 scale. Judge-based analytical task performance; not a general intelligence or guaranteed success rate.

Low
50.3 · $0.1748 / task
Medium
51.3 · $0.2708 / task
High
54.7 · $0.3874 / task
Extra high · pick
61.3 · $0.5817 / task
Max
57.0 · $0.9845 / task

Near-best pick: Extra high within 1 point of the best score. Highest-to-lowest score gap: 11.0 points.

Explore this study ↗

Original source ↗

All results and the exact settings tested

A dash means the study did not report that result. This table compares only the versions and settings tested on the same questions in this study.

GPT-6 Sol · Analytics · DataBench v1.1 · Analytics in the Hex agent harness
Effort / budgetAnalytics scoreMeasured USD / taskMedian seconds / taskExact source configuration
Low50.3$0.174897.6GPT-6 Sol · Low
Medium51.3$0.2708146.2GPT-6 Sol · Medium
High54.7$0.3874238.0GPT-6 Sol · High
Extra high61.3$0.5817326.7GPT-6 Sol · XHigh
Max57.0$0.9845617.5GPT-6 Sol · Max

Download this study’s data (CSV) ↓

EXPLORATORY CASE STUDY

Math and logic · 44-problem Codex study

Correct answers out of 88 observed runs on 44 fixed problems, repeated twice. Repeats are not 88 independent questions; reported confidence intervals overlap for the near-ceiling models.

Medium
96.6
High · pick
97.7

Near-best pick: High within 1 point of the best score. Highest-to-lowest score gap: 1.1 points.

Explore this study ↗

Original source ↗

All results and the exact settings tested

A dash means the study did not report that result. This table compares only the versions and settings tested on the same questions in this study.

GPT-6 Sol · Math and logic · 44-problem Codex study · 44 fixed problems × 2 repeats · Codex Pro · concurrency 3 · medium versus high
Effort / budgetAnswers correctMedian seconds / taskReported 95% accuracy intervalExact source configuration
Medium96.67.990.5–98.8%gpt-6-sol / medium / 44-problem Codex test
High97.78.192.1–99.4%gpt-6-sol / high / 44-problem Codex test

Download this study’s data (CSV) ↓

Data: Joonlab · Codex subscription study. CC BY 4.0 ↗. AI Agent Store aggregates the published rows and adapts their labels. These are the same 44 problems at both settings. A small difference, often driven by one question, is a reason to test your tasks rather than a universal effort recommendation. Duration is the source median including network and queue time; no API cost is estimated.

EXPLORATORY CASE STUDY

Five efforts · one arithmetic prompt

Correct answers in three repeats of one prompt: count ordered integer pairs from 1 to 60 whose product is a perfect square; expected answer 158. One miss changes the score by 33.3 points. This is not a general reasoning benchmark.

Low
66.7
Medium
66.7
High · pick
100.0
Extra high
66.7
Max
100.0

Near-best pick: High within 1 point of the best score. Highest-to-lowest score gap: 33.3 points.

Explore this study ↗

Original source ↗

All results and the exact settings tested

A dash means the study did not report that result. This table compares only the versions and settings tested on the same questions in this study.

GPT-6 Sol · Five efforts · one arithmetic prompt · One fixed arithmetic prompt × 3 repeats · Codex Pro · concurrency 3
Effort / budgetArithmetic runs correctMedian seconds / taskAverage output tokensExact source configuration
Low66.79.4385gpt-6-sol / low / reasoning prompt
Medium66.714.3590gpt-6-sol / medium / reasoning prompt
High100.013.3652gpt-6-sol / high / reasoning prompt
Extra high66.714.4759gpt-6-sol / xhigh / reasoning prompt
Max100.022.61,184gpt-6-sol / max / reasoning prompt

Download this study’s data (CSV) ↓

Data: Joonlab · Codex subscription study. CC BY 4.0 ↗. AI Agent Store aggregates the published rows and adapts their labels. One arithmetic question and three repeats per setting cannot establish general accuracy. The displayed output and reasoning tokens are means of raw runs; durations are medians. All five Sol6.1 settings answered this question correctly, so extra reasoning showed no accuracy gain on this example. These observations predate Ultrafast and do not compare service tiers.

Reasoning effort, explained

Which GPT-6 Sol thinking level is most efficient?

Extra high is the lowest-cost option within 1 point of the best analytics score in Hex DataBench v1.1. Max trails the best tested score by 4.3 points. This allows a score up to 1 point below the best result in the first listed study. Change the study, task and allowed score gap above to explore another comparison. It is a shortlist for testing your own workload.

Which GPT-6 Sol effort settings are compared?

Low, Medium, High, Extra high, Max appear in the collected studies. Each chart only includes modes tested together in that study. These published labels do not establish that every endpoint or application exposes every setting.

Does more effort improve GPT-6 Sol?

In Hex DataBench v1.1, Extra high to Max lowers the observed score by 4.3 points. The overall tested range is 11.0 points. These are observed differences, not proof that extra thinking caused the decline.

How much more does high effort cost for GPT-6 Sol?

Use the A/B selector and measured-cost calculator when the source reports dollar costs. For your own agent, enter average input, visible output and thinking tokens in the token calculator. Higher effort is adaptive, so the label itself cannot tell you the bill. Missing costs stay missing.

Keep comparing

AI Agent Store · Model comparisons · Data reviewed 2026-10-15Sources, limitations & corrections ↗