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gpt-oss 120B (high)

OpenAI · open weights · writing benchmark

#112 of 130 Elo 839 Overall 67.6 Open weights
Rank
#112 of 130
Writing Elo
839 ±53
Overall
67.6 / 100
Cost / task
$0.002 per script
Family
OpenAI 32nd of 36
Type
Open 32nd of 47
Consistency
± 5.7 swingier than most
Avg tokens
19.1k in+out
Latency
91s per call
Family check:GPT-5.6 Sol (ultra) is OpenAI's best writer here, +20.8 overall vs this config for $0.135 more per script.

The short version

gpt-oss 120B (high) sits at #112 of 130 on ToneBench, toward the value end of the board, with a writing Elo of 839 and an overall score of 67.6 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 32nd of 36. GPT-5.6 Sol (ultra) is the family's top writer here, about 1477 Elo ahead, so this config trades some quality for whatever it saves you in cost or speed.

Among open-weights models, it comes in 32nd of 47. Open weights still trail the closed frontier on pure voice fidelity, and you can see that in the gap at the top.

What it does best is Length Discipline: it ranks 66th on that dimension at 71.6, above the board average. Its softer spot is Substance & Value (60.6, 120th), which is the thing to watch if that metric matters most for your use.

It was uneven across the 9 scripts. Its best run was the product release announcement / personal observation (72.8) and its weakest was the personal technical walkthrough / agentic workflow case study (60.5), a spread of about 12 points. Worth knowing if your writing skews toward one of those formats.

On cost, it runs about $0.002/task. For that money it beats 6 models that cost noticeably more.

If you're tuning reasoning effort, we also tested gpt-oss 120B at other settings. None of them beat this config; the closest is gpt-oss 120B (Elo 797), so the only question is how much quality you want to trade for cost or speed.

Skill profile

The shape is the story: the further a corner reaches, the stronger that dimension. Biggest edge over the board: Length Discipline (+4.4); furthest behind: Substance & Value (-18.1).

50Tone?Craft?Substance?Flow?YouTube?Hook?Length?Anti-Slop?Cues?
gpt-oss 120B (high)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 · -8.9 vs avg
best · Claude Opus 5 (max effort) · 91.269.4± 3.7 · 112thboard avg · 78.3
Writing Craft ?13% weight · -7.7 vs avg
best · Claude Opus 5 (max effort) · 91.171.2± 3.2 · 111thboard avg · 78.9
Substance & Value ?15% weight · -18.1 vs avg
best · Claude Opus 5 (max effort) · 90.660.6± 6.0 · 120thboard avg · 78.7
Flow & Emotion ?14% weight · -9.7 vs avg
best · Claude Opus 5 (max effort) · 90.464.7± 4.4 · 110thboard avg · 74.4
YouTube Structure ?12% weight · -7.9 vs avg
best · Claude Opus 5 (max effort) · 89.665.5± 4.5 · 100thboard avg · 73.3
Hook ?10% weight · -8.1 vs avg
best · Claude Opus 5 (max effort) · 92.072.1± 4.3 · 113thboard avg · 80.2
Length Discipline ?8% weight · +4.4 vs avg
best · GPT-5.6 Sol (ultra) · 94.371.6± 10.7 · 66thboard avg · 67.2
Anti-Slop ?5% weight · -8.9 vs avg
best · Claude Fable 5 (max effort + 4.8 fallback) · 93.773.8± 3.5 · 103rdboard avg · 82.8
Visual Cues ?4% weight · -12.7 vs avg
best · GPT-5.6 Sol (xhigh) · 91.461.9± 13.9 · 105thboard 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
64.4
out of 100
Article 2
news-analysis / skeptical explainer
71.2
out of 100
Article 3
personal roadmap / opinion
67.6
out of 100
Article 4
short explainer
70.5
out of 100
Article 5
news-analysis / opinion explainer
67.2
out of 100
Article 6
founder announcement / personal origin story
72.0
out of 100
Article 7
personal technical walkthrough / agentic workflow case study
60.5
out of 100
Article 8
product release announcement / personal observation
72.8
out of 100
Article 9
career guide / hiring analysis
61.8
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-oss 120B (high) varies by ± 5.7 points between runs versus a board median of ± 3.8, so it is swingier than the typical model here, worth knowing if you need repeatable output.

Its most volatile dimension is Tone & Voice (± 3.7 vs a board median of ± 2.2): two runs of the same brief can land visibly different tone & voice scores.

MetricThis modelBoard medianVerdict
Tone & Voice ?69.4 ± 3.7± 2.2swingier than most
Writing Craft ?71.2 ± 3.2± 2.0swingier than most
Substance & Value ?60.6 ± 6.0± 2.6swingier than most
Flow & Emotion ?64.7 ± 4.4± 2.6swingier than most
YouTube Structure ?65.5 ± 4.5± 3.6typical
Hook ?72.1 ± 4.3± 3.0typical
Length Discipline ?71.6 ± 10.7± 8.6typical
Anti-Slop ?73.8 ± 3.5± 2.6typical
Visual Cues ?61.9 ± 13.9± 4.7swingier 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
91sslower than the board median of 70s
Prompt tokens in
10.7kstyle guide + brief + research packet
Tokens out
8.4kwell above the board median (thinks a lot)
Cost per script
$0.002 ± 0.001measured from actual billed tokens
List price used
$0.037 / $0.17 per M tokinput / output

What each judge scored it

The published overall of 67.6 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 15.3 points on its overall. That gap is wider than typical (board median 9.0): DeepSeek V4 Flash rates it noticeably higher than Claude Opus 5. Read the per-metric numbers knowing the consensus sits between two real opinions. How the panel works: methodology.

Claude Opus 5
Anthropic
59.8
GPT-5.6 Sol (medium)
OpenAI
67.9
DeepSeek V4 Flash
DeepSeek
75.0

How we ran gpt-oss 120B (high)

Frequently asked questions

How good is gpt-oss 120B (high) at writing?

On ToneBench it ranks #112 of 130 with a writing Elo of 839 and an overall score of 67.6/100. 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-oss 120B (high) the best OpenAI model for writing?

Not quite. Within OpenAI it ranks 32nd of 36; GPT-5.6 Sol (ultra) is the family's best writer here.

Is gpt-oss 120B (high) good value for the money?

It costs about $0.002/task. Nothing meaningfully cheaper outscores it, which puts it on the value side of the board.

What are gpt-oss 120B (high)'s strengths and weaknesses?

Its strongest dimension is Length Discipline (66th on the board, 71.6). Its weakest is Substance & Value (120th on the board, 60.6). The full nine-metric breakdown is on this page.

Does gpt-oss 120B (high) write some formats better than others?

Yes. Its best of our 9 scripts was the product release announcement / personal observation (72.8) and its weakest was the personal technical walkthrough / agentic workflow case study (60.5).

How consistent is gpt-oss 120B (high) between runs?

We run every script 5 times. gpt-oss 120B (high)'s overall score varies by about ±5.7 points between runs, versus a board median of ±3.8. That is swingier than typical, so expect more draft-to-draft variation. The full per-metric variability table is on this page.

How was gpt-oss 120B (high) evaluated?

Via OpenRouter using the exact model/route id openai/gpt-oss-120b at reasoning_effort high, 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-oss 120B (high) open source?

Yes, it is an open-weights model. Among open-weights models it ranks 32nd of 47 for writing.

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