Qwen3-Max
Alibaba (Qwen) · proprietary · writing benchmark
The short version
Qwen3-Max sits at #91 of 130 on ToneBench, toward the value end of the board, with a writing Elo of 1224 and an overall score of 74.5 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 4th of 10. Qwen3.8 Max is the family's top writer here, about 642 Elo ahead, so this config trades some quality for whatever it saves you in cost or speed.
Among proprietary models, it comes in 67th of 83. That ranking is against the stronger half of the board: closed models still set the pace on voice fidelity here.
What it does best is Length Discipline: it ranks 68th on that dimension at 71.0, above the board average. Its softer spot is Anti-Slop (67.4, 118th), 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 (80.8) and its weakest was the personal technical walkthrough / agentic workflow case study (69.8), a spread of about 11 points. Worth knowing if your writing skews toward one of those formats.
On cost, it runs about $0.017/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 7 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 (+3.9); furthest behind: Anti-Slop (-15.3).
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.
Per-article scores
The same 9 real scripts every current-ranked model writes, scored individually. Different formats stress different skills.
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-Max varies by ± 3.8 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 (± 4.7 vs a board median of ± 2.6): two runs of the same brief can land visibly different substance & value scores.
| Metric | This model | Board median | Verdict |
|---|---|---|---|
| Tone & Voice ? | 78.5 ± 2.4 | ± 2.2 | typical |
| Writing Craft ? | 78.7 ± 2.2 | ± 2.0 | typical |
| Substance & Value ? | 72.2 ± 4.7 | ± 2.6 | swingier than most |
| Flow & Emotion ? | 73.8 ± 3.2 | ± 2.6 | typical |
| YouTube Structure ? | 68.0 ± 5.2 | ± 3.6 | typical |
| Hook ? | 81.8 ± 3.5 | ± 3.0 | typical |
| Length Discipline ? | 71.0 ± 5.2 | ± 8.6 | typical |
| Anti-Slop ? | 67.4 ± 2.3 | ± 2.6 | typical |
| Visual Cues ? | 68.7 ± 6.8 | ± 4.7 | typical |
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.
What each judge scored it
The published overall of 74.5 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 12.9 points on its overall. A typical amount of judge disagreement for this board. How the panel works: methodology.
How we ran Qwen3-Max
- Accessed viaOpenRouter · model page ↗
- Exact model / route id
qwen/qwen3-max(provider default reasoning) - Audited route overrideOpenRouter ·
qwen/qwen3-maxforautomated_video_workflow(Task-7 exact OpenRouter endpoint pin alibaba/fp8) - Generations5 independent runs × 9 scripts = 45 drafts, stored immutably after generation
- Run dates2026-07-29 → 2026-08-11
- Judges3-judge panel: Claude Opus 5, high effort (Anthropic) + DeepSeek V4 Flash (OpenRouter) + GPT-5.6 Sol, medium reasoning (Codex CLI): every draft scored independently by all three with the identical rubric, blind to model identity, evidence quotes required before each metric score; published score = per-metric consensus mean, verified with a Bradley-Terry refit (methodology)
- Samplingprovider-default sampling, no fine-tuning, no system-prompt changes; every current-ranked model gets the identical brief, style contract and research packet
- What stays privatethe exact rubric and any non-public reference material; source-publication timing is disclosed for exceptions (why)
Frequently asked questions
How good is Qwen3-Max at writing?
On ToneBench it ranks #91 of 130 with a writing Elo of 1224 and an overall score of 74.5/100. 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-Max the best Alibaba (Qwen) model for writing?
Not quite. Within Alibaba (Qwen) it ranks 4th of 10; Qwen3.8 Max is the family's best writer here.
Is Qwen3-Max good value for the money?
It costs about $0.017/task. DeepSeek V4 Flash (native chat alias) scores higher for less, so it is not the value pick.
What are Qwen3-Max's strengths and weaknesses?
Its strongest dimension is Length Discipline (68th on the board, 71.0). Its weakest is Anti-Slop (118th on the board, 67.4). The full nine-metric breakdown is on this page.
Does Qwen3-Max write some formats better than others?
Yes. Its best of our 9 scripts was the founder announcement / personal origin story (80.8) and its weakest was the personal technical walkthrough / agentic workflow case study (69.8).
How consistent is Qwen3-Max between runs?
We run every script 5 times. Qwen3-Max's overall score varies by about ±3.8 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 Qwen3-Max evaluated?
Via OpenRouter using the exact model/route id qwen/qwen3-max, 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-Max open source?
No, it is a proprietary (closed-weights) model. Among proprietary models it ranks 67th of 83 for writing.