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gpt-oss 120B

OpenAI · open weights · writing benchmark

#113 of 130 Elo 797 Overall 66.8 Open weights
Rank
#113 of 130
Writing Elo
797 ±43
Overall
66.8 / 100
Cost / task
$0.001 per script
Family
OpenAI 33rd of 36
Type
Open 33rd of 47
Consistency
± 5.2 typical spread
Avg tokens
13.0k in+out
Latency
37s per call
Family check:GPT-5.6 Sol (ultra) is OpenAI's best writer here, +21.6 overall vs this config for $0.136 more per script.

The short version

gpt-oss 120B sits at #113 of 130 on ToneBench, toward the value end of the board, with a writing Elo of 797 and an overall score of 66.8 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 33rd of 36. GPT-5.6 Sol (ultra) is the family's top writer here, about 1518 Elo ahead, so this config trades some quality for whatever it saves you in cost or speed.

Among open-weights models, it comes in 33rd 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 73rd on that dimension at 67.5, above the board average. Its softer spot is Substance & Value (61.3, 119th), 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 founder announcement / personal origin story (74.1) and its weakest was the personal technical walkthrough / agentic workflow case study (59.0), a spread of about 15 points. Worth knowing if your writing skews toward one of those formats.

On cost, it runs about $0.001/task. For that money it beats 12 models that cost noticeably more.

If you're tuning reasoning effort, we also tested gpt-oss 120B at other settings. The strongest of those on the board is gpt-oss 120B (high) (Elo 839), 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: Length Discipline (+0.3); furthest behind: Substance & Value (-17.4).

50Tone?Craft?Substance?Flow?YouTube?Hook?Length?Anti-Slop?Cues?
gpt-oss 120BBoard 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 · -9.6 vs avg
best · Claude Opus 5 (max effort) · 91.268.7± 3.1 · 113thboard avg · 78.3
Writing Craft ?13% weight · -7.5 vs avg
best · Claude Opus 5 (max effort) · 91.171.4± 2.8 · 109thboard avg · 78.9
Substance & Value ?15% weight · -17.4 vs avg
best · Claude Opus 5 (max effort) · 90.661.3± 5.2 · 119thboard avg · 78.7
Flow & Emotion ?14% weight · -10.3 vs avg
best · Claude Opus 5 (max effort) · 90.464.1± 3.3 · 112thboard avg · 74.4
YouTube Structure ?12% weight · -8.6 vs avg
best · Claude Opus 5 (max effort) · 89.664.7± 3.9 · 103rdboard avg · 73.3
Hook ?10% weight · -7.4 vs avg
best · Claude Opus 5 (max effort) · 92.072.8± 4.0 · 112thboard avg · 80.2
Length Discipline ?8% weight · +0.3 vs avg
best · GPT-5.6 Sol (ultra) · 94.367.5± 9.1 · 73rdboard avg · 67.2
Anti-Slop ?5% weight · -11.1 vs avg
best · Claude Fable 5 (max effort + 4.8 fallback) · 93.771.6± 2.4 · 106thboard avg · 82.8
Visual Cues ?4% weight · -17.3 vs avg
best · GPT-5.6 Sol (xhigh) · 91.457.2± 12.9 · 113thboard 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
63.2
out of 100
Article 2
news-analysis / skeptical explainer
69.4
out of 100
Article 3
personal roadmap / opinion
63.0
out of 100
Article 4
short explainer
68.3
out of 100
Article 5
news-analysis / opinion explainer
66.9
out of 100
Article 6
founder announcement / personal origin story
74.1
out of 100
Article 7
personal technical walkthrough / agentic workflow case study
59.0
out of 100
Article 8
product release announcement / personal observation
71.2
out of 100
Article 9
career guide / hiring analysis
66.2
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-oss 120B varies by ± 5.2 points between runs versus a board median of ± 3.8, so it is about as repeatable as the typical model on the board.

Its most volatile dimension is Substance & Value (± 5.2 vs a board median of ± 2.6): two runs of the same brief can land visibly different substance & value scores.

MetricThis modelBoard medianVerdict
Tone & Voice ?68.7 ± 3.1± 2.2typical
Writing Craft ?71.4 ± 2.8± 2.0typical
Substance & Value ?61.3 ± 5.2± 2.6swingier than most
Flow & Emotion ?64.1 ± 3.3± 2.6typical
YouTube Structure ?64.7 ± 3.9± 3.6typical
Hook ?72.8 ± 4.0± 3.0typical
Length Discipline ?67.5 ± 9.1± 8.6typical
Anti-Slop ?71.6 ± 2.4± 2.6typical
Visual Cues ?57.2 ± 12.9± 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
37sfaster than the board median of 70s
Prompt tokens in
10.6kstyle guide + brief + research packet
Tokens out
2.5kscript + any reasoning tokens
Cost per script
$0.001 ± 0.000measured from actual billed tokens
List price used
$0.037 / $0.17 per M tokinput / output

What each judge scored it

The published overall of 66.8 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 15.8 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
58.4
GPT-5.6 Sol (medium)
OpenAI
67.8
DeepSeek V4 Flash
DeepSeek
74.2

How we ran gpt-oss 120B

Frequently asked questions

How good is gpt-oss 120B at writing?

On ToneBench it ranks #113 of 130 with a writing Elo of 797 and an overall score of 66.8/100. 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 the best OpenAI model for writing?

Not quite. Within OpenAI it ranks 33rd of 36; GPT-5.6 Sol (ultra) is the family's best writer here.

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

It costs about $0.001/task. Nothing meaningfully cheaper outscores it, which puts it on the value side of the board.

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

Its strongest dimension is Length Discipline (73rd on the board, 67.5). Its weakest is Substance & Value (119th on the board, 61.3). The full nine-metric breakdown is on this page.

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

Yes. Its best of our 9 scripts was the founder announcement / personal origin story (74.1) and its weakest was the personal technical walkthrough / agentic workflow case study (59.0).

How consistent is gpt-oss 120B between runs?

We run every script 5 times. gpt-oss 120B's overall score varies by about ±5.2 points between runs, versus a board median of ±3.8. That is typical consistency for this board. The full per-metric variability table is on this page.

How was gpt-oss 120B evaluated?

Via OpenRouter using the exact model/route id openai/gpt-oss-120b, 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 open source?

Yes, it is an open-weights model. Among open-weights models it ranks 33rd of 47 for writing.

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