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ds DeepSeek V4 Pro (xhigh)

DeepSeek · open weights · writing benchmark

#60 of 130 Elo 1601 Overall 80.5 Open weights
Rank
#60 of 130
Writing Elo
1601 ±71
Overall
80.5 / 100
Cost / task
$0.014 per script
Family
DeepSeek 2nd of 8
Type
Open 9th of 47
Consistency
± 3.7 typical spread
Avg tokens
21.7k in+out
Latency
163s per call
Family check:DeepSeek V4 Flash 0731 is DeepSeek's best writer here, +3.7 overall vs this config for $0.009 less per script.

The short version

DeepSeek V4 Pro (xhigh) sits at #60 of 130 on ToneBench, in the middle of the pack, with a writing Elo of 1601 and an overall score of 80.5 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 DeepSeek it ranks 2nd of 8. DeepSeek V4 Flash 0731 is the family's top writer here, about 354 Elo ahead, so this config trades some quality for whatever it saves you in cost or speed.

Among open-weights models, it comes in 9th 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 44th on that dimension at 80.5, well above the board average. Its softer spot is Anti-Slop (79.4, 91st), 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 (84.1) and its weakest was the personal technical walkthrough / agentic workflow case study (76.2), a spread of about 8 points. Worth knowing if your writing skews toward one of those formats.

On cost, it runs about $0.014/task. DeepSeek V4 Flash 0731 scores higher for less money, at $0.005/task, so on pure value this config is not the frontier. Still, it beats 23 models that cost noticeably more.

If you're tuning reasoning effort, we also tested DeepSeek V4 Pro at other settings. None of them beat this config; the closest is DeepSeek V4 Pro (default) (Elo 1590), 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 (+13.3); furthest behind: Anti-Slop (-3.4).

50Tone?Craft?Substance?Flow?YouTube?Hook?Length?Anti-Slop?Cues?
DeepSeek V4 Pro (xhigh)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 · +3.9 vs avg
best · Claude Opus 5 (max effort) · 91.282.2± 2.4 · 61stboard avg · 78.3
Writing Craft ?13% weight · +3.3 vs avg
best · Claude Opus 5 (max effort) · 91.182.2± 2.4 · 61stboard avg · 78.9
Substance & Value ?15% weight · +2.3 vs avg
best · Claude Opus 5 (max effort) · 90.681.0± 3.4 · 66thboard avg · 78.7
Flow & Emotion ?14% weight · +4.1 vs avg
best · Claude Opus 5 (max effort) · 90.478.5± 3.5 · 61stboard avg · 74.4
YouTube Structure ?12% weight · +3.6 vs avg
best · Claude Opus 5 (max effort) · 89.676.9± 4.2 · 66thboard avg · 73.3
Hook ?10% weight · +4.4 vs avg
best · Claude Opus 5 (max effort) · 92.084.6± 3.2 · 55thboard avg · 80.2
Length Discipline ?8% weight · +13.3 vs avg
best · GPT-5.6 Sol (ultra) · 94.380.5± 12.3 · 44thboard avg · 67.2
Anti-Slop ?5% weight · -3.4 vs avg
best · Claude Fable 5 (max effort + 4.8 fallback) · 93.779.4± 4.7 · 91stboard avg · 82.8
Visual Cues ?4% weight · -0.9 vs avg
best · GPT-5.6 Sol (xhigh) · 91.473.6± 7.6 · 86thboard 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
79.1
out of 100
Article 2
news-analysis / skeptical explainer
82.8
out of 100
Article 3
personal roadmap / opinion
79.0
out of 100
Article 4
short explainer
80.3
out of 100
Article 5
news-analysis / opinion explainer
80.9
out of 100
Article 6
founder announcement / personal origin story
84.1
out of 100
Article 7
personal technical walkthrough / agentic workflow case study
76.2
out of 100
Article 8
product release announcement / personal observation
83.2
out of 100
Article 9
career guide / hiring analysis
79.0
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, DeepSeek V4 Pro (xhigh) varies by ± 3.7 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 Anti-Slop (± 4.7 vs a board median of ± 2.6): two runs of the same brief can land visibly different anti-slop scores.

MetricThis modelBoard medianVerdict
Tone & Voice ?82.2 ± 2.4± 2.2typical
Writing Craft ?82.2 ± 2.4± 2.0typical
Substance & Value ?81.0 ± 3.4± 2.6typical
Flow & Emotion ?78.5 ± 3.5± 2.6typical
YouTube Structure ?76.9 ± 4.2± 3.6typical
Hook ?84.6 ± 3.2± 3.0typical
Length Discipline ?80.5 ± 12.3± 8.6typical
Anti-Slop ?79.4 ± 4.7± 2.6swingier than most
Visual Cues ?73.6 ± 7.6± 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
163sslower than the board median of 70s
Prompt tokens in
10.9kstyle guide + brief + research packet
Tokens out
10.8kwell above the board median (thinks a lot)
Cost per script
$0.014 ± 0.006measured from actual billed tokens
List price used
$0.435 / $0.87 per M tokinput / output

What each judge scored it

The published overall of 80.5 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 7.2 points on its overall. A typical amount of judge disagreement for this board. How the panel works: methodology.

Claude Opus 5
Anthropic
76.0
GPT-5.6 Sol (medium)
OpenAI
82.4
DeepSeek V4 Flash
DeepSeek
83.2

How we ran DeepSeek V4 Pro (xhigh)

Frequently asked questions

How good is DeepSeek V4 Pro (xhigh) at writing?

On ToneBench it ranks #60 of 130 with a writing Elo of 1601 and an overall score of 80.5/100. 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 DeepSeek V4 Pro (xhigh) the best DeepSeek model for writing?

Not quite. Within DeepSeek it ranks 2nd of 8; DeepSeek V4 Flash 0731 is the family's best writer here.

Is DeepSeek V4 Pro (xhigh) good value for the money?

It costs about $0.014/task. DeepSeek V4 Flash 0731 scores higher for less, so it is not the value pick.

What are DeepSeek V4 Pro (xhigh)'s strengths and weaknesses?

Its strongest dimension is Length Discipline (44th on the board, 80.5). Its weakest is Anti-Slop (91st on the board, 79.4). The full nine-metric breakdown is on this page.

Does DeepSeek V4 Pro (xhigh) write some formats better than others?

Yes. Its best of our 9 scripts was the founder announcement / personal origin story (84.1) and its weakest was the personal technical walkthrough / agentic workflow case study (76.2).

How consistent is DeepSeek V4 Pro (xhigh) between runs?

We run every script 5 times. DeepSeek V4 Pro (xhigh)'s overall score varies by about ±3.7 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 DeepSeek V4 Pro (xhigh) evaluated?

Via OpenRouter using the exact model/route id deepseek/deepseek-v4-pro at reasoning_effort xhigh, 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 DeepSeek V4 Pro (xhigh) open source?

Yes, it is an open-weights model. Among open-weights models it ranks 9th of 47 for writing.

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