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K Kimi K2 Thinking

Moonshot (Kimi) · open weights · writing benchmark

#76 of 130 Elo 1437 Overall 77.6 Open weights
Rank
#76 of 130
Writing Elo
1437 ±50
Overall
77.6 / 100
Cost / task
$0.025 per script
Family
Moonshot (Kimi) 5th of 6
Type
Open 17th of 47
Consistency
± 4.3 typical spread
Avg tokens
18.1k in+out
Latency
190s per call
Family check:Kimi K3 is Moonshot (Kimi)'s best writer here, +11.8 overall vs this config for $0.238 more per script.

The short version

Kimi K2 Thinking sits at #76 of 130 on ToneBench, toward the value end of the board, with a writing Elo of 1437 and an overall score of 77.6 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 Moonshot (Kimi) it ranks 5th of 6. Kimi K3 is the family's top writer here, about 1000 Elo ahead, so this config trades some quality for whatever it saves you in cost or speed.

Among open-weights models, it comes in 17th 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 49th on that dimension at 76.8, well above the board average. Its softer spot is Visual Cues (66.5, 96th), 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 (83.2) and its weakest was the personal technical walkthrough / agentic workflow case study (71.8), a spread of about 11 points. Worth knowing if your writing skews toward one of those formats.

On cost, it runs about $0.025/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 8 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 (+9.6); furthest behind: Visual Cues (-8.0).

50Tone?Craft?Substance?Flow?YouTube?Hook?Length?Anti-Slop?Cues?
Kimi K2 ThinkingBoard 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 · +1.7 vs avg
best · Claude Opus 5 (max effort) · 91.280.0± 2.3 · 69thboard avg · 78.3
Writing Craft ?13% weight · +1.3 vs avg
best · Claude Opus 5 (max effort) · 91.180.2± 1.9 · 75thboard avg · 78.9
Substance & Value ?15% weight · -2.3 vs avg
best · Claude Opus 5 (max effort) · 90.676.4± 3.0 · 95thboard avg · 78.7
Flow & Emotion ?14% weight · +1.2 vs avg
best · Claude Opus 5 (max effort) · 90.475.6± 2.6 · 77thboard avg · 74.4
YouTube Structure ?12% weight · +1.0 vs avg
best · Claude Opus 5 (max effort) · 89.674.3± 4.3 · 77thboard avg · 73.3
Hook ?10% weight · +3.0 vs avg
best · Claude Opus 5 (max effort) · 92.083.2± 3.0 · 71stboard avg · 80.2
Length Discipline ?8% weight · +9.6 vs avg
best · GPT-5.6 Sol (ultra) · 94.376.8± 12.9 · 49thboard avg · 67.2
Anti-Slop ?5% weight · -4.5 vs avg
best · Claude Fable 5 (max effort + 4.8 fallback) · 93.778.2± 2.8 · 95thboard avg · 82.8
Visual Cues ?4% weight · -8.0 vs avg
best · GPT-5.6 Sol (xhigh) · 91.466.5± 12.2 · 96thboard 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
74.4
out of 100
Article 2
news-analysis / skeptical explainer
81.1
out of 100
Article 3
personal roadmap / opinion
74.2
out of 100
Article 4
short explainer
76.4
out of 100
Article 5
news-analysis / opinion explainer
78.4
out of 100
Article 6
founder announcement / personal origin story
80.8
out of 100
Article 7
personal technical walkthrough / agentic workflow case study
71.8
out of 100
Article 8
product release announcement / personal observation
83.2
out of 100
Article 9
career guide / hiring analysis
78.3
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, Kimi K2 Thinking varies by ± 4.3 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 Length Discipline (± 12.9 vs a board median of ± 8.6): two runs of the same brief can land visibly different length discipline scores.

MetricThis modelBoard medianVerdict
Tone & Voice ?80.0 ± 2.3± 2.2typical
Writing Craft ?80.2 ± 1.9± 2.0typical
Substance & Value ?76.4 ± 3.0± 2.6typical
Flow & Emotion ?75.6 ± 2.6± 2.6typical
YouTube Structure ?74.3 ± 4.3± 3.6typical
Hook ?83.2 ± 3.0± 3.0typical
Length Discipline ?76.8 ± 12.9± 8.6swingier than most
Anti-Slop ?78.2 ± 2.8± 2.6typical
Visual Cues ?66.5 ± 12.2± 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
190sslower than the board median of 70s
Prompt tokens in
10.7kstyle guide + brief + research packet
Tokens out
7.4kwell above the board median (thinks a lot)
Cost per script
$0.025 ± 0.011measured from actual billed tokens
List price used
$0.6 / $2.5 per M tokinput / output

What each judge scored it

The published overall of 77.6 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 7.4 points on its overall. A typical amount of judge disagreement for this board. How the panel works: methodology.

Claude Opus 5
Anthropic
72.8
GPT-5.6 Sol (medium)
OpenAI
79.8
DeepSeek V4 Flash
DeepSeek
80.3

How we ran Kimi K2 Thinking

Frequently asked questions

How good is Kimi K2 Thinking at writing?

On ToneBench it ranks #76 of 130 with a writing Elo of 1437 and an overall score of 77.6/100. 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 Kimi K2 Thinking the best Moonshot (Kimi) model for writing?

Not quite. Within Moonshot (Kimi) it ranks 5th of 6; Kimi K3 is the family's best writer here.

Is Kimi K2 Thinking good value for the money?

It costs about $0.025/task. DeepSeek V4 Flash (native chat alias) scores higher for less, so it is not the value pick.

What are Kimi K2 Thinking's strengths and weaknesses?

Its strongest dimension is Length Discipline (49th on the board, 76.8). Its weakest is Visual Cues (96th on the board, 66.5). The full nine-metric breakdown is on this page.

Does Kimi K2 Thinking write some formats better than others?

Yes. Its best of our 9 scripts was the product release announcement / personal observation (83.2) and its weakest was the personal technical walkthrough / agentic workflow case study (71.8).

How consistent is Kimi K2 Thinking between runs?

We run every script 5 times. Kimi K2 Thinking's overall score varies by about ±4.3 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 Kimi K2 Thinking evaluated?

Via OpenRouter using the exact model/route id moonshotai/kimi-k2-thinking, 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 Kimi K2 Thinking open source?

Yes, it is an open-weights model. Among open-weights models it ranks 17th of 47 for writing.

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