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GPT-5.6 Sol (none)

OpenAI · proprietary · writing benchmark

#23 of 130 Elo 2164 Overall 87.2 Proprietary
Rank
#23 of 130
Writing Elo
2164 ±47
Overall
87.2 / 100
Cost / task
$0.15 per script
Family
OpenAI 8th of 36
Type
Closed 21st of 83
Consistency
± 1.3 steadier than most
Avg tokens
15.5k in+out
Latency
86s per call
Family check:GPT-5.6 Sol (ultra) is OpenAI's best writer here, +1.2 overall vs this config for $0.013 less per script.

The short version

GPT-5.6 Sol (none) sits at #23 of 130 on ToneBench, in the middle of the pack, with a writing Elo of 2164 and an overall score of 87.2 out of 100. We measured it by having it write all 9 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 8th of 36. GPT-5.6 Sol (ultra) is the family's top writer here, about 152 Elo ahead, so this config trades some quality for whatever it saves you in cost or speed.

Among proprietary models, it comes in 21st of 83. 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 45 drafts the overall score only moves ± 1.3 points run to run, versus a board median of ± 3.8. What you get on the first try is close to what you get every try.

What it does best is Visual Cues: it ranks 6th on that dimension at 90.6, well above the board average. Its softer spot is Length Discipline (81.0, 42nd), which is the thing to watch if that metric matters most for your use.

It held steady across all 9 scripts, with its best run on the career guide / hiring analysis (88.2). Consistency like that is underrated, honestly, since it means fewer surprises when you actually put it to work.

On cost, it runs about $0.15/task. GPT-5.6 Terra (ultra) scores higher for less money, at $0.065/task, so on pure value this config is not the frontier.

If you're tuning reasoning effort, we also tested GPT-5.6 Sol at other settings. The strongest of those on the board is GPT-5.6 Sol (high) (Elo 2315), so it is worth checking whether more or less thinking moves the needle before you lock in this one.

Skill profile

The shape is the story: the further a corner reaches, the stronger that dimension. Biggest edge over the board: Visual Cues (+16.1); smallest edge: Hook (+7.1).

50Tone?Craft?Substance?Flow?YouTube?Hook?Length?Anti-Slop?Cues?
GPT-5.6 Sol (none)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 130 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 · +9.2 vs avg
best · Claude Opus 5 (max effort) · 91.287.5± 1.4 · 25thboard avg · 78.3
Writing Craft ?13% weight · +9.1 vs avg
best · Claude Opus 5 (max effort) · 91.188.0± 1.1 · 18thboard avg · 78.9
Substance & Value ?15% weight · +10.8 vs avg
best · Claude Opus 5 (max effort) · 90.689.5± 1.4 · 14thboard avg · 78.7
Flow & Emotion ?14% weight · +10.9 vs avg
best · Claude Opus 5 (max effort) · 90.485.3± 1.8 · 21stboard avg · 74.4
YouTube Structure ?12% weight · +12.3 vs avg
best · Claude Opus 5 (max effort) · 89.685.6± 2.0 · 26thboard avg · 73.3
Hook ?10% weight · +7.1 vs avg
best · Claude Opus 5 (max effort) · 92.087.3± 2.1 · 24thboard avg · 80.2
Length Discipline ?8% weight · +13.8 vs avg
best · GPT-5.6 Sol (ultra) · 94.381.0± 8.7 · 42ndboard avg · 67.2
Anti-Slop ?5% weight · +10.5 vs avg
best · Claude Fable 5 (max effort + 4.8 fallback) · 93.793.2± 1.1 · 9thboard avg · 82.8
Visual Cues ?4% weight · +16.1 vs avg
best · GPT-5.6 Sol (xhigh) · 91.490.6± 1.5 · 6thboard avg · 74.5

Per-article scores

The same 9 real scripts every current-ranked model writes, scored individually. Different formats stress different skills.

Article 1
opinion / warning explainer
86.9
out of 100
Article 2
news-analysis / skeptical explainer
88.1
out of 100
Article 3
personal roadmap / opinion
87.5
out of 100
Article 4
short explainer
86.3
out of 100
Article 5
news-analysis / opinion explainer
87.2
out of 100
Article 6
founder announcement / personal origin story
87.3
out of 100
Article 7
personal technical walkthrough / agentic workflow case study
86.1
out of 100
Article 8
product release announcement / personal observation
87.2
out of 100
Article 9
career guide / hiring analysis
88.2
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-5.6 Sol (none) varies by ± 1.3 points between runs versus a board median of ± 3.8, so it is noticeably steadier than the typical model here.

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

MetricThis modelBoard medianVerdict
Tone & Voice ?87.5 ± 1.4± 2.2typical
Writing Craft ?88.0 ± 1.1± 2.0steadier than most
Substance & Value ?89.5 ± 1.4± 2.6steadier than most
Flow & Emotion ?85.3 ± 1.8± 2.6typical
YouTube Structure ?85.6 ± 2.0± 3.6steadier than most
Hook ?87.3 ± 2.1± 3.0typical
Length Discipline ?81.0 ± 8.7± 8.6typical
Anti-Slop ?93.2 ± 1.1± 2.6steadier than most
Visual Cues ?90.6 ± 1.5± 4.7steadier 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
86s
Prompt tokens in
12.6kstyle guide + brief + research packet
Tokens out
2.9kscript + any reasoning tokens
Cost per script
$0.150 ± 0.071measured from actual billed tokens
List price used
$5 / $30 per M tokinput / output

What each judge scored it

The published overall of 87.2 is the consensus of three family-disjoint judges scoring the same 45 stored drafts blind with the identical rubric. The highest and lowest judge differ by 9.1 points on its overall. A typical amount of judge disagreement for this board. How the panel works: methodology.

Claude Opus 5
Anthropic
83.2
GPT-5.6 Sol (medium)
OpenAI
92.3
DeepSeek V4 Flash
DeepSeek
86.1

How we ran GPT-5.6 Sol (none)

Frequently asked questions

How good is GPT-5.6 Sol (none) at writing?

On ToneBench it ranks #23 of 130 with a writing Elo of 2164 and an overall score of 87.2/100. That score comes from writing our 9 real YouTube scripts five times each and scoring every draft blind against our own finished versions across nine writing dimensions.

Is GPT-5.6 Sol (none) the best OpenAI model for writing?

Not quite. Within OpenAI it ranks 8th of 36; GPT-5.6 Sol (ultra) is the family's best writer here.

Is GPT-5.6 Sol (none) good value for the money?

It costs about $0.15/task. GPT-5.6 Terra (ultra) scores higher for less, so it is not the value pick.

What are GPT-5.6 Sol (none)'s strengths and weaknesses?

Its strongest dimension is Visual Cues (6th on the board, 90.6). Its weakest is Length Discipline (42nd on the board, 81.0). The full nine-metric breakdown is on this page.

Does GPT-5.6 Sol (none) write some formats better than others?

It was fairly even across all 9 scripts, topping out on the career guide / hiring analysis (88.2).

How consistent is GPT-5.6 Sol (none) between runs?

We run every script 5 times. GPT-5.6 Sol (none)'s overall score varies by about ±1.3 points between runs, versus a board median of ±3.8. That makes it one of the steadier models we test. The full per-metric variability table is on this page.

How was GPT-5.6 Sol (none) evaluated?

Via Codex CLI (OpenAI subscription) using the exact model/route id gpt-5.6-sol at reasoning_effort none, run on 2026-07-29. 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-5.6 Sol (none) open source?

No, it is a proprietary (closed-weights) model. Among proprietary models it ranks 21st of 83 for writing.

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