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GPT-6 Sol (max)

OpenAI · proprietary · writing benchmark

#31 of 167 Elo 2166 Overall 88.0 Proprietary
Rank
#31 of 167
Writing Elo
2166 ±37
Overall
88.0 / 100
Cost / task
$0.112 per script
Family
OpenAI 2nd of 44
Type
Closed 27th of 114
Consistency
± 1.3 steadier than most
Avg tokens
20.3k in+out
Latency
171s per call
Family check:GPT-5.6 Sol (ultra) is OpenAI's best writer here, +0.1 overall vs this config for $0.250 more per script.

The short version

GPT-6 Sol (max) sits at #31 of 167 on ToneBench, in the middle of the pack, with a writing Elo of 2166 and an overall score of 88.0 out of 100. We measured it by having it write all 10 of our real YouTube scripts, five times each, then scoring every draft blind against our own finished versions. Here is how it shook out.

Within OpenAI it ranks 2nd of 44. GPT-5.6 Sol (ultra) is the family's top writer here, about 21 Elo ahead, so this config trades some quality for whatever it saves you in cost or speed.

Among proprietary models, it comes in 27th of 114. That ranking is against the stronger half of the board: closed models still set the pace on voice fidelity here.

One thing that stands out: it is unusually consistent. Across its 50 drafts the overall score only moves ± 1.3 points run to run, versus a board median of ± 2.7. What you get on the first try is close to what you get every try.

What it does best is Anti-Slop: it ranks 6th on that dimension at 94.1, well above the board average. Its softer spot is Tone & Voice (85.8, 55th), which is the thing to watch if that metric matters most for your use.

It was uneven across the 10 scripts. Its best run was the career guide / hiring analysis (89.4) and its weakest was the product release announcement / personal observation (86.2), a spread of about 3 points. Worth knowing if your writing skews toward one of those formats.

On cost, it runs about $0.112/task. GLM-5.3 Flash scores higher for less money, at $0.007/task, so on pure value this config is not the frontier. Still, it beats 17 models that cost noticeably more.

Skill profile

The shape is the story: the further a corner reaches, the stronger that dimension. Biggest edge over the board: Length Discipline (+20.4); smallest edge: Hook (+5.3).

50Tone?Craft?Substance?Flow?YouTube?Hook?Length?Anti-Slop?Cues?
GPT-6 Sol (max)Board averageBoard best per metricMax possible (100)

Per-metric scores

Nine writing dimensions, each scored 0–100 and blended by the editorial weight shown. Rank is against all 167 current-ranked models. The thick bar is this model; the thin lines above and below are the current field's best model (darker) and average (lighter) on the same scale. The small ± number is its run-to-run variation.

Tone & Voice ?19% weight · +7.3 vs avg
best · Claude Opus 5.5 (max effort) · 91.085.8± 1.4 · 55thboard avg · 78.6
Writing Craft ?13% weight · +7.3 vs avg
best · Claude Opus 5.5 (max effort) · 91.587.8± 1.1 · 42ndboard avg · 80.5
Substance & Value ?15% weight · +9.5 vs avg
best · Claude Opus 5.5 (xhigh) · 90.788.9± 1.1 · 9thboard avg · 79.4
Flow & Emotion ?14% weight · +9.4 vs avg
best · Claude Opus 5.5 (max effort) · 90.986.4± 1.3 · 34thboard avg · 77.0
YouTube Structure ?12% weight · +11.1 vs avg
best · Claude Opus 5.5 (max effort) · 91.787.9± 1.3 · 26thboard avg · 76.7
Hook ?10% weight · +5.3 vs avg
best · Claude Opus 5.5 (max effort) · 91.286.9± 1.8 · 41stboard avg · 81.6
Length Discipline ?8% weight · +20.4 vs avg
best · Claude Opus 5.5 (max effort) · 97.691.2± 4.8 · 13thboard avg · 70.8
Anti-Slop ?5% weight · +9.9 vs avg
best · Claude Opus 5.5 (max effort) · 94.994.1± 0.8 · 6thboard avg · 84.2
Visual Cues ?4% weight · +12.2 vs avg
best · GPT-5.6 Sol (ultra) · 90.189.2± 1.1 · 8thboard avg · 77.0

Per-article scores

The same 10 real scripts every current-ranked model writes, scored individually. Different formats stress different skills.

Article 1
opinion / warning explainer
86.6
out of 100
Article 2
news-analysis / skeptical explainer
87.9
out of 100
Article 3
personal roadmap / opinion
88.1
out of 100
Article 4
short explainer
88.4
out of 100
Article 5
news-analysis / opinion explainer
87.0
out of 100
Article 6
founder announcement / personal origin story
88.9
out of 100
Article 7
personal technical walkthrough / agentic workflow case study
88.3
out of 100
Article 8
product release announcement / personal observation
86.2
out of 100
Article 9
career guide / hiring analysis
89.4
out of 100
Article 10
engineering process walkthrough / presentation adaptation
88.6
out of 100

Consistency: run-to-run variability

Every cell on this page is the mean of 5 independent runs per script; the ± numbers are the run-to-run standard deviation. Overall, GPT-6 Sol (max) varies by ± 1.3 points between runs versus a board median of ± 2.7, so it is noticeably steadier than the typical model here.

Its steadiest is Substance & Value (± 1.1 vs ± 2.0 board median), which you can rely on run after run.

MetricThis modelBoard medianVerdict
Tone & Voice ?85.8 ± 1.4± 1.7typical
Writing Craft ?87.8 ± 1.1± 1.5typical
Substance & Value ?88.9 ± 1.1± 2.0steadier than most
Flow & Emotion ?86.4 ± 1.3± 1.8typical
YouTube Structure ?87.9 ± 1.3± 2.9steadier than most
Hook ?86.9 ± 1.8± 2.0typical
Length Discipline ?91.2 ± 4.8± 8.6steadier than most
Anti-Slop ?94.1 ± 0.8± 2.1steadier than most
Visual Cues ?89.2 ± 1.1± 3.2steadier than most

Measured, not modeled

Numbers we log on every run and rarely talk about. None of these affect the writing scores; cost and latency are informational.

Latency per script
171sslower than the board median of 70s
Prompt tokens in
11.3kstyle guide + brief + research packet
Tokens out
9.0kwell above the board median (thinks a lot)
Cost per script
$0.112 ± 0.028output measured incl. thinking; input priced as the prompt billed once
List price used
$2 / $10 per M tokinput / output

What each judge scored it

The published overall of 88.0 is the consensus of three family-disjoint judges scoring the same 50 stored drafts blind with the identical rubric. The highest and lowest judge differ by 8.0 points on its overall. A typical amount of judge disagreement for this board. How the panel works: methodology.

Claude Opus 5
Anthropic
86.8
GPT-5.6 Sol (medium)
OpenAI
92.5
DeepSeek V4.1 Flash
DeepSeek
84.5

How we ran GPT-6 Sol (max)

Frequently asked questions

How good is GPT-6 Sol (max) at writing?

On ToneBench it ranks #31 of 167 with a writing Elo of 2166 and an overall score of 88.0/100. That score comes from writing our 10 real YouTube scripts five times each and scoring every draft blind against our own finished versions across nine writing dimensions.

Is GPT-6 Sol (max) the best OpenAI model for writing?

Not quite. Within OpenAI it ranks 2nd of 44; GPT-5.6 Sol (ultra) is the family's best writer here.

Is GPT-6 Sol (max) good value for the money?

It costs about $0.112/task. GLM-5.3 Flash scores higher for less, so it is not the value pick.

What are GPT-6 Sol (max)'s strengths and weaknesses?

Its strongest dimension is Anti-Slop (6th on the board, 94.1). Its weakest is Tone & Voice (55th on the board, 85.8). The full nine-metric breakdown is on this page.

Does GPT-6 Sol (max) write some formats better than others?

Yes. Its best of our 10 scripts was the career guide / hiring analysis (89.4) and its weakest was the product release announcement / personal observation (86.2).

How consistent is GPT-6 Sol (max) between runs?

We run every script 5 times. GPT-6 Sol (max)'s overall score varies by about ±1.3 points between runs, versus a board median of ±2.7. That makes it one of the steadier models we test. The full per-metric variability table is on this page.

How was GPT-6 Sol (max) evaluated?

Via Codex CLI (OpenAI subscription) using the exact model/route id gpt-6-sol at reasoning_effort max, run on 2026-09-25. 5 runs per script, provider-default sampling, no fine-tuning; every draft scored blind with a fixed rubric by a three-family judge panel. Full details in the 'How we ran it' section and the methodology.

Is GPT-6 Sol (max) open source?

No, it is a proprietary (closed-weights) model. Among proprietary models it ranks 27th of 114 for writing.

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