Towards AITowards AIToneBench

Qwen3 235B A22B

Alibaba (Qwen) · open weights · writing benchmark

#100 of 130 Elo 1040 Overall 70.8 Open weights
Rank
#100 of 130
Writing Elo
1040 ±73
Overall
70.8 / 100
Cost / task
$0.003 per script
Family
Alibaba (Qwen) 5th of 10
Type
Open 26th of 47
Consistency
± 5.6 swingier than most
Avg tokens
13.8k in+out
Latency
58s per call
Family check:Qwen3.8 Max is Alibaba (Qwen)'s best writer here, +12.6 overall vs this config for $0.147 more per script.

The short version

Qwen3 235B A22B sits at #100 of 130 on ToneBench, toward the value end of the board, with a writing Elo of 1040 and an overall score of 70.8 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 Alibaba (Qwen) it ranks 5th of 10. Qwen3.8 Max is the family's top writer here, about 826 Elo ahead, so this config trades some quality for whatever it saves you in cost or speed.

Among open-weights models, it comes in 26th 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 59th on that dimension at 73.7, well above the board average. Its softer spot is Anti-Slop (66.3, 121st), 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 (75.3) and its weakest was the news-analysis / opinion explainer (63.4), a spread of about 12 points. Worth knowing if your writing skews toward one of those formats.

On cost, it runs about $0.003/task. DeepSeek V4 Flash (native chat alias) scores higher for less money, at $0.002/task, so on pure value this config is not the frontier. Still, it beats 11 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 (+6.6); furthest behind: Visual Cues (-19.3).

50Tone?Craft?Substance?Flow?YouTube?Hook?Length?Anti-Slop?Cues?
Qwen3 235B A22BBoard 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 · -2.0 vs avg
best · Claude Opus 5 (max effort) · 91.276.3± 3.2 · 90thboard avg · 78.3
Writing Craft ?13% weight · -4.1 vs avg
best · Claude Opus 5 (max effort) · 91.174.8± 3.0 · 104thboard avg · 78.9
Substance & Value ?15% weight · -9.6 vs avg
best · Claude Opus 5 (max effort) · 90.669.1± 5.2 · 110thboard avg · 78.7
Flow & Emotion ?14% weight · -6.5 vs avg
best · Claude Opus 5 (max effort) · 90.467.9± 5.3 · 104thboard avg · 74.4
YouTube Structure ?12% weight · -11.9 vs avg
best · Claude Opus 5 (max effort) · 89.661.4± 8.1 · 112thboard avg · 73.3
Hook ?10% weight · -1.0 vs avg
best · Claude Opus 5 (max effort) · 92.079.2± 4.6 · 96thboard avg · 80.2
Length Discipline ?8% weight · +6.6 vs avg
best · GPT-5.6 Sol (ultra) · 94.373.7± 15.0 · 59thboard avg · 67.2
Anti-Slop ?5% weight · -16.5 vs avg
best · Claude Fable 5 (max effort + 4.8 fallback) · 93.766.3± 2.8 · 121stboard avg · 82.8
Visual Cues ?4% weight · -19.3 vs avg
best · GPT-5.6 Sol (xhigh) · 91.455.2± 10.8 · 116thboard 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
70.2
out of 100
Article 2
news-analysis / skeptical explainer
72.2
out of 100
Article 3
personal roadmap / opinion
72.1
out of 100
Article 4
short explainer
68.5
out of 100
Article 5
news-analysis / opinion explainer
63.4
out of 100
Article 6
founder announcement / personal origin story
72.0
out of 100
Article 7
personal technical walkthrough / agentic workflow case study
69.5
out of 100
Article 8
product release announcement / personal observation
75.3
out of 100
Article 9
career guide / hiring analysis
74.0
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, Qwen3 235B A22B varies by ± 5.6 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 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 ?76.3 ± 3.2± 2.2typical
Writing Craft ?74.8 ± 3.0± 2.0typical
Substance & Value ?69.1 ± 5.2± 2.6swingier than most
Flow & Emotion ?67.9 ± 5.3± 2.6swingier than most
YouTube Structure ?61.4 ± 8.1± 3.6swingier than most
Hook ?79.2 ± 4.6± 3.0swingier than most
Length Discipline ?73.7 ± 15.0± 8.6swingier than most
Anti-Slop ?66.3 ± 2.8± 2.6typical
Visual Cues ?55.2 ± 10.8± 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
58s
Prompt tokens in
10.8kstyle guide + brief + research packet
Tokens out
2.9kscript + any reasoning tokens
Cost per script
$0.003 ± 0.001measured from actual billed tokens
List price used
$0.09 / $0.55 per M tokinput / output

What each judge scored it

The published overall of 70.8 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 13.2 points on its overall. A typical amount of judge disagreement for this board. How the panel works: methodology.

Claude Opus 5
Anthropic
63.7
GPT-5.6 Sol (medium)
OpenAI
71.8
DeepSeek V4 Flash
DeepSeek
76.8

How we ran Qwen3 235B A22B

Frequently asked questions

How good is Qwen3 235B A22B at writing?

On ToneBench it ranks #100 of 130 with a writing Elo of 1040 and an overall score of 70.8/100. 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 Qwen3 235B A22B the best Alibaba (Qwen) model for writing?

Not quite. Within Alibaba (Qwen) it ranks 5th of 10; Qwen3.8 Max is the family's best writer here.

Is Qwen3 235B A22B good value for the money?

It costs about $0.003/task. DeepSeek V4 Flash (native chat alias) scores higher for less, so it is not the value pick.

What are Qwen3 235B A22B's strengths and weaknesses?

Its strongest dimension is Length Discipline (59th on the board, 73.7). Its weakest is Anti-Slop (121st on the board, 66.3). The full nine-metric breakdown is on this page.

Does Qwen3 235B A22B write some formats better than others?

Yes. Its best of our 9 scripts was the product release announcement / personal observation (75.3) and its weakest was the news-analysis / opinion explainer (63.4).

How consistent is Qwen3 235B A22B between runs?

We run every script 5 times. Qwen3 235B A22B's overall score varies by about ±5.6 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 Qwen3 235B A22B evaluated?

Via OpenRouter using the exact model/route id qwen/qwen3-235b-a22b-2507, 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 Qwen3 235B A22B open source?

Yes, it is an open-weights model. Among open-weights models it ranks 26th of 47 for writing.

← Back to the full ToneBench leaderboard