Muse Wonder ranks #16 of 80 models on the October 2026 ToneBench board through its best configuration, Muse Wonder (max). This setting, Muse Wonder (high), is #58 of 132 configurations, with a Writing Score of 76.7/100 and a Writing Elo of 1664. One script costs $0.149 at API list price.
Last updated , from board data generated at 20:08 UTC.
Rank, scores, the nine metrics, the 10 reference scripts, cost and setup for one
configuration (a model at one reasoning setting). Key Results sums it up; the section links below it jump to the detail.
Model Rank ?
#16 of 80 modelsthrough Muse Wonder (max); this setting is #58 of 132 configurations
Writing Score ?
76.7 out of 100
Writing Elo ?
1664 95% range 1600 to 1724
Cost per Script
$0.149 at API list price
Key Results
StandingMuse Wonder ranks #16 of 80 models through its best configuration, Muse Wonder (max). This setting is #58 of 132 configurations by Writing Elo (1664), in the middle third of the board. Its 95% range (1600 to 1724) overlaps 19 other configurations, ranked #52 to #71, so its exact place among them is not settled.
MetricsBest-ranked: Continuity & Emotion (81.4, 21st of 132 configurations, +4.3 against the board median). Lowest-ranked: Length Adherence (41.1, 121st of 132 configurations, -41.7 against the board median).
ScriptsFrom 73.2 on Script 10 (engineering process walkthrough) to 79.7 on Script 2 (news-analysis): a 6.5-point spread across the 10 reference scripts.
ConsistencyIts Writing Score moves ± 3.1 between drafts of the same script, against ± 2.8 for the median configuration: typical.
ValueGPT-6 Luna (high) ranks about the same (their Elo ranges overlap) and costs about $0.0028 per script, against $0.149 per script for this one.
Louis's PickI'd pay about 16 cents more per script for Muse Wonder (max).
More Context Behind These Results
Writing Elo comes from comparing its average on each script with every other configuration's average on that same script; a gap smaller than the draft-to-draft variation counts as a draw (what the ranges can and cannot show).
On Continuity & Emotion, its best-ranked metric, its sections hold together as one story more often than the typical configuration's. Length Adherence ranks in the bottom half (121st of 132 configurations), so plan on trimming or padding to reach the target length.
The script format moves its score a lot. If most of your scripts look like its best or weakest format, that result is a better guide than the average.
It outranks 3 configurations that cost at least 50% more.
Among proprietary models, Muse Wonder is 12th of 47. This setting is 48th of 91 proprietary configurations. The best open-weight configuration, GLM-5.3 (max) at configuration #15, outranks it.
Lab
Meta 1st of 4 modelsthis setting 2nd of 7 configurations
Weights
Proprietary 12th of 47 modelsthis setting 48th of 91 configurations
Consistency
± 3.1 typical spread
Average Tokens
18.0k input + output
Time per Script
0.9 min average, retries included
Highest-Ranked in This LabMuse Wonder (max) ranks highest of the Meta configurations by Writing Elo, with a Writing Score +3.9 against this configuration, for about 16 cents more per script.
Each corner is one metric on a 0 to 100 scale; the further out, the higher the score. A corner outside the dashed line beats the board median. Hover or tap a point for its exact score, and a metric name for what it rewards.
Muse Wonder (high)Board medianBoard best per metricMax possible (100)
Scores by Metric
Nine metrics, each scored 0 to 100 and weighted into the Writing Score; the weight sits under each name. Rank is out of all 132 ranked configurations.
Score colors:Strong: 82 and upMiddle: 65 to 81.9Weak: under 65
This modelBoard best (upper line)Board median (lower line)±: spread between drafts?: what the metric rewards
Tone & Voice Match ?19% weight · +3.5 vs median
board best 82.8 · Claude Opus 5.5 (max effort)77.0± 2.0 · 45thboard median 73.4
Writing Craft & Clarity ?13% weight · +1.9 vs median
board best 83.2 · Claude Opus 5.5 (xhigh)75.9± 1.7 · 52ndboard median 74.0
Substance, Accuracy & Value ?15% weight · +4.9 vs median
board best 88.4 · Claude Opus 5.5 (xhigh)85.7± 1.3 · 24thboard median 80.7
Continuity & Emotion ?14% weight · +4.3 vs median
board best 85.7 · Claude Opus 5.5 (max effort)81.4± 1.2 · 21stboard median 77.1
YouTube Best Practices ?12% weight · +5.0 vs median
board best 84.4 · Claude Opus 5.5 (xhigh)80.1± 2.0 · 23rdboard median 75.1
Hook Strength ?10% weight · +0.5 vs median
board best 83.7 · Claude Opus 5.5 (max effort)79.8± 3.0 · 57thboard median 79.2
Length Adherence ?8% weight · -41.7 vs median
board best 98.8 · Claude Sonnet 5.5 (max effort)41.1± 23.8 · 121stboard median 82.8
Slop Score ?5% weight · +1.5 vs median
board best 89.0 · GPT-6 Sol (medium)82.1± 1.5 · 53rdboard median 80.6
Visual Cue Quality ?4% weight · -0.2 vs median
board best 85.9 · Claude Opus 5.5 (max effort)74.1± 3.7 · 69thboard median 74.2
Scores by Reference Script
Every ranked configuration writes five drafts for each of the same 10 briefs, and each score is the mean of those drafts. The rank and board median compare it with every configuration on that script, which separates a weak result from a hard script. The result on the format closest to your own work is the most relevant.
Script 1
opinion / warning explainer
75.4
out of 100
76th of 132 configurations on this script · board median 76.1
Script 2
news-analysis / skeptical explainer
79.7
out of 100
46th of 132 configurations on this script · board median 77.6
Script 3
personal roadmap / opinion
75.9
out of 100
68th of 132 configurations on this script · board median 76.1
Script 4
short explainer
74.1
out of 100
66th of 132 configurations on this script · board median 74.1
Script 5
news-analysis / opinion explainer
79.1
out of 100
51st of 132 configurations on this script · board median 76.6
Script 6
founder announcement / personal origin story
78.7
out of 100
67th of 132 configurations on this script · board median 78.8
Script 7
personal technical walkthrough / agentic workflow case study
76.7
out of 100
66th of 132 configurations on this script · board median 76.7
Script 8
product release announcement / personal observation
76.4
out of 100
77th of 132 configurations on this script · board median 78.3
Script 9
career guide / hiring analysis
77.5
out of 100
71st of 132 configurations on this script · board median 78.4
Script 10
engineering process walkthrough / presentation adaptation
73.2
out of 100
71st of 132 configurations on this script · board median 73.6
Consistency Between Drafts
Every score on this page is the mean of 5 drafts per script. The ± is the standard deviation between those drafts: the larger it is, the more two drafts of the same script can differ.
Compared with the typical model, it varies most on Length Adherence: ± 23.8 between drafts against ± 7.1, so two drafts of the same script can score quite differently there. On the same comparison, it's steadiest on Substance, Accuracy & Value: ± 1.3 between drafts against ± 2.3.
Consistency by Metric
Metric
This model
Board median
Verdict
Tone & Voice Match ?
77.0 ± 2.0
± 2.0
typical
Writing Craft & Clarity ?
75.9 ± 1.7
± 1.6
typical
Substance, Accuracy & Value ?
85.7 ± 1.3
± 2.3
steadier than most
Continuity & Emotion ?
81.4 ± 1.2
± 1.5
typical
YouTube Best Practices ?
80.1 ± 2.0
± 2.5
typical
Hook Strength ?
79.8 ± 3.0
± 2.8
typical
Length Adherence ?
41.1 ± 23.8
± 7.1
more variable than most
Slop Score ?
82.1 ± 1.5
± 1.7
typical
Visual Cue Quality ?
74.1 ± 3.7
± 3.0
typical
Cost, Time and Tokens per Script
Logged on every run; none of these figures affects the Writing Score. Time is the average time to one accepted script, retries included. Cost is one script at the API list price.
Time per Script
0.9 minfaster than the board median of 1.5 min
Prompt tokens in
13.2kstyle guide + brief + research packet
Tokens Out
4.8kscript + any reasoning tokens
Cost per Script
$0.149measured from actual billed tokens; varies ± 0.038 between drafts
List Price Used
$4 / $20input / output, per million tokens
Scores by Judge
Four judges score the same 50 stored drafts blind against the same rubric: three LLM judges from three labs, plus Jev, a typed judge from TypeSafe that rates each metric on five described quality levels. No single judge's taste decides the result. The Writing Score of 76.7 combines their scores with the parts computed in code (Length Adherence and half of the Slop Score). The highest and lowest judge are 10.8 points apart on its Writing Score. That is close to the board median of 13.8. Each judge also has its own scale, so every card shows that judge's score against its average across the board. How the panel works.
Claude Opus 5.5 (medium)
Anthropic
72.4
+4.9 against its board average of 67.4
GLM 5.3 Flash
Z.ai
83.2
+1.1 against its board average of 82.1
GPT-6.1 Sol (medium)
OpenAI
74.0
+3.3 against its board average of 70.7
Jev 1.13
TypeSafe
77.1
+3.7 against its board average of 73.3
Evaluation Setup
How this exact configuration was run and judged: route, model ID, dates, sampling and prompt.
Exact model / route idmeta/muse-wonder at reasoning level: high.
Generations5 independent runs × 10 scripts = 50 drafts, stored after generation and never edited.
Run dates2026-10-13.
JudgesClaude Opus 5.5 at medium effort through the Claude Code subscription, GPT-6.1 Sol at medium reasoning through the Codex CLI, GLM 5.3 Flash through OpenRouter, and Jev 1.13 from TypeSafe. One call per judge per draft. All four score every draft on their own, blind to which model wrote it. The three LLM judges use the identical rubric and have to quote evidence before they score a metric. Jev answers the same rubric as one question per metric, choosing among five described quality levels, and writes no text. Seven metrics are the plain average of the four judges. Length is computed from the spoken word count, and Slop is half computed (lexical scans minus the spoken-dash penalty) and half judged. The Writing Elo is cross-checked with a Bradley-Terry fit of the same pairwise results (methodology).
Sampling and promptThe provider's default sampling, with no fine-tuning and no system-prompt changes. Every current-ranked model gets the same prompt, about 13,000 tokens (the count shifts a bit with each model's tokenizer): a style guide built from Louis's voice and storytelling guides, the target length, and the brief with its research packet. Generation is closed-book on every route: the prompt is the only source, with no web search, browsing, code execution, file access or other tool (generation).
What stays privateThe exact rubric and any non-public reference material. Each script is normally benchmarked before its video is published, which lowers the odds that a model has seen the reference, though it does not rule it out (why).
Frequently Asked Questions
How Good Is Muse Wonder (high) at Writing?
Muse Wonder ranks #16 of 80 models on ToneBench through its best configuration, Muse Wonder (max). This configuration is #58 of 132 configurations, in the middle third of the board, with a Writing Elo of 1664 and a Writing Score of 76.7/100. The ranks come from full YouTube scripts written in the voice of Louis-François Bouchard and judged blind, with the channel's finished script as the reference. The benchmark measures long-form scripted writing, so the result does not carry over to every kind of text.
Is Muse Wonder (high) the Best Meta Model for Writing?
Muse Wonder is the top Meta model, #16 of 80 models, through Muse Wonder (max). This setting is 2nd of 7 Meta configurations, about 341 Elo behind it.
Is Muse Wonder (high) Good Value for the Money?
It costs about $0.149 per script. GPT-6 Luna (high) ranks about the same, inside the overlap of their Elo ranges, and costs less.
What Are the Strengths and Weaknesses of Muse Wonder (high)?
Its best-ranked metric is Continuity & Emotion (81.4, 21st of 132 configurations, +4.3 against the board median), and its lowest-ranked is Length Adherence (41.1, 121st of 132, -41.7). The Scores by Metric section shows the board median and the board's best for each one.
How Was Muse Wonder (high) Evaluated?
It was run through OpenRouter, with the exact model/route ID meta/muse-wonder at reasoning effort high, first run on 2026-10-13. It wrote each script 5 times with the provider's default sampling and no fine-tuning. The Evaluation Setup section and the methodology page have the details.
Does Muse Wonder (high) Have Open Weights?
No. It is a proprietary model: its weights are not public. Among proprietary configurations it is 48th of 91 for writing.