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Llama 4 Maverick

Meta · open weights · writing benchmark

#116 of 130 Elo 584 Overall 60.7 Open weights
Rank
#116 of 130
Writing Elo
584 ±50
Overall
60.7 / 100
Cost / task
$0.003 per script
Family
Meta 1st of 3
Type
Open 36th of 47
Consistency
± 8.4 swingier than most
Avg tokens
11.5k in+out
Latency
30s per call

The short version

Llama 4 Maverick sits at #116 of 130 on ToneBench, toward the value end of the board, with a writing Elo of 584 and an overall score of 60.7 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.

Inside Meta, this is the strongest writer we tested. It edges out the other 2 Meta configs on the board, so if you're staying in this family for voice work, this is the one to reach for.

Among open-weights models, it comes in 36th of 47. Open weights still trail the closed frontier on pure voice fidelity, and you can see that in the gap at the top.

Worth knowing before you rely on it: this model is swingy. Its overall score moves ± 8.4 points between runs of the same brief, versus a board median of ± 3.8. A great draft and a mediocre one can come from the identical prompt. The shaded bands on the metric bars below show where that volatility lives.

What it does best is Visual Cues: it ranks 110th on that dimension at 58.2, well below the board average. Its softer spot is Length Discipline (29.3, 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 (73.0) and its weakest was the personal technical walkthrough / agentic workflow case study (51.0), a spread of about 22 points. Worth knowing if your writing skews toward one of those formats.

On cost, it runs about $0.003/task. Cohere Command A Reasoning scores higher for less money, at $0/task, so on pure value this config is not the frontier. Still, it beats 3 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: Writing Craft (-9.8); furthest behind: Length Discipline (-37.9).

50Tone?Craft?Substance?Flow?YouTube?Hook?Length?Anti-Slop?Cues?
Llama 4 MaverickBoard 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 · -15.2 vs avg
best · Claude Opus 5 (max effort) · 91.263.1± 3.4 · 117thboard avg · 78.3
Writing Craft ?13% weight · -9.8 vs avg
best · Claude Opus 5 (max effort) · 91.169.2± 2.9 · 113thboard avg · 78.9
Substance & Value ?15% weight · -10.8 vs avg
best · Claude Opus 5 (max effort) · 90.667.9± 4.4 · 111thboard avg · 78.7
Flow & Emotion ?14% weight · -14.8 vs avg
best · Claude Opus 5 (max effort) · 90.459.6± 4.1 · 116thboard avg · 74.4
YouTube Structure ?12% weight · -20.4 vs avg
best · Claude Opus 5 (max effort) · 89.652.9± 4.9 · 118thboard avg · 73.3
Hook ?10% weight · -12.7 vs avg
best · Claude Opus 5 (max effort) · 92.067.6± 6.0 · 117thboard avg · 80.2
Length Discipline ?8% weight · -37.9 vs avg
best · GPT-5.6 Sol (ultra) · 94.329.3± 5.8 · 119thboard avg · 67.2
Anti-Slop ?5% weight · -13.9 vs avg
best · Claude Fable 5 (max effort + 4.8 fallback) · 93.768.9± 5.2 · 116thboard avg · 82.8
Visual Cues ?4% weight · -16.3 vs avg
best · GPT-5.6 Sol (xhigh) · 91.458.2± 5.9 · 110thboard 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
56.0
out of 100
Article 2
news-analysis / skeptical explainer
70.5
out of 100
Article 3
personal roadmap / opinion
60.0
out of 100
Article 4
short explainer
55.7
out of 100
Article 5
news-analysis / opinion explainer
55.3
out of 100
Article 6
founder announcement / personal origin story
73.0
out of 100
Article 7
personal technical walkthrough / agentic workflow case study
51.0
out of 100
Article 8
product release announcement / personal observation
68.8
out of 100
Article 9
career guide / hiring analysis
56.1
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, Llama 4 Maverick varies by ± 8.4 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 Tone & Voice (± 3.4 vs a board median of ± 2.2): two runs of the same brief can land visibly different tone & voice scores.

MetricThis modelBoard medianVerdict
Tone & Voice ?63.1 ± 3.4± 2.2swingier than most
Writing Craft ?69.2 ± 2.9± 2.0typical
Substance & Value ?67.9 ± 4.4± 2.6swingier than most
Flow & Emotion ?59.6 ± 4.1± 2.6swingier than most
YouTube Structure ?52.9 ± 4.9± 3.6typical
Hook ?67.6 ± 6.0± 3.0swingier than most
Length Discipline ?29.3 ± 5.8± 8.6typical
Anti-Slop ?68.9 ± 5.2± 2.6swingier than most
Visual Cues ?58.2 ± 5.9± 4.7typical

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
30sfaster than the board median of 70s
Prompt tokens in
10.5kstyle guide + brief + research packet
Tokens out
1.0kscript + any reasoning tokens
Cost per script
$0.003 ± 0.000measured from actual billed tokens
List price used
$0.2 / $0.8 per M tokinput / output

What each judge scored it

The published overall of 60.7 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 11.8 points on its overall. A typical amount of judge disagreement for this board. How the panel works: methodology.

Claude Opus 5
Anthropic
53.2
GPT-5.6 Sol (medium)
OpenAI
65.0
DeepSeek V4 Flash
DeepSeek
63.9

How we ran Llama 4 Maverick

Frequently asked questions

How good is Llama 4 Maverick at writing?

On ToneBench it ranks #116 of 130 with a writing Elo of 584 and an overall score of 60.7/100. 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 Llama 4 Maverick the best Meta model for writing?

Yes. Among the Meta configs we tested, Llama 4 Maverick is the strongest writer on the board.

Is Llama 4 Maverick good value for the money?

It costs about $0.003/task. Cohere Command A Reasoning scores higher for less, so it is not the value pick.

What are Llama 4 Maverick's strengths and weaknesses?

Its strongest dimension is Visual Cues (110th on the board, 58.2). Its weakest is Length Discipline (119th on the board, 29.3). The full nine-metric breakdown is on this page.

Does Llama 4 Maverick write some formats better than others?

Yes. Its best of our 9 scripts was the founder announcement / personal origin story (73.0) and its weakest was the personal technical walkthrough / agentic workflow case study (51.0).

How consistent is Llama 4 Maverick between runs?

We run every script 5 times. Llama 4 Maverick's overall score varies by about ±8.4 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 Llama 4 Maverick evaluated?

Via OpenRouter using the exact model/route id meta-llama/llama-4-maverick, 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 Llama 4 Maverick open source?

Yes, it is an open-weights model. Among open-weights models it ranks 36th of 47 for writing.

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