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Model Comparison

GPT-6.1 Sol vs Muse Wonder

GPT-6.1 Sol (max) leads Muse Wonder (max) by 199 Elo, and their 95% ranges sit 127 Elo apart. Among 80 models, each ranked by its best configuration, GPT-6.1 Sol is #8 and Muse Wonder is #16. Cost per script: $0.239 for GPT-6.1 Sol (max) and $0.309 for Muse Wonder (max).

Last updated , from board data generated at 20:08 UTC.

GPT-6.1 Sol
2204 Writing Elo of GPT-6.1 Sol (max), its best configuration#8 of 80 models · 82.4/100 Writing Score · $0.239 per script5 configurations on the board
Muse Wonder
2005 Writing Elo of Muse Wonder (max), its best configuration#16 of 80 models · 80.6/100 Writing Score · $0.309 per script3 configurations on the board

Picks and Verdict

PickGPT-6.1 Sol

GPT-6.1 Sol (low)

Pick GPT-6.1 Sol (low) for volume, since at $0.052 and 1.5 minutes it ranks 79 Elo above Muse's best with separate ranges, at about a sixth of the price.

PickMuse Wonder

Muse Wonder (max)

Pick Muse Wonder (max) if Continuity & Emotion is the metric you watch, since its 81.5 beats every GPT-6.1 Sol setting, at $0.309 a script.

GPT-6.1 Sol rates above Muse Wonder at every setting, though not always by a margin the board can confirm. GPT-6.1 Sol (max) leads Muse Wonder (max) by 199 Elo with 95% ranges 127 apart, the #8 model of 80 against the #16 model, and costs less, $0.239 against $0.309. The catch is time: 10.2 minutes a script, where Muse is done in 2.0. GPT-6.1 Sol (low), at $0.052 and 1.5 minutes, rates 79 Elo above Muse at max for about a sixth of the price, and their ranges just clear each other, by 8 Elo. Sol's high and medium don't: they sit 37 and 19 Elo up, and the board can't separate either from Muse's best. At high, the level name they share below max, Sol leads by 378 Elo with separate ranges. Muse's high and adaptive settings fall far behind its max, mostly on Length Adherence. Between the two max settings, Sol hits the length 15.5 points better and has cleaner slop and visual cues, by more than four points each. Muse keeps continuity, 2.3 points ahead, and a small YouTube structure edge. I'd use Sol at low for volume and xhigh, which overlaps max for $0.199, for scripts I publish.

Disclosure: GPT-6.1 Sol comes from the same lab as one of the four judges, GPT-6.1 Sol. The other three sit outside its lab, so it is never scored by its own lab alone (how the panel works). The judge analysis measures how much each judge favors its own lab.

How to Read the Writing Score, Writing Elo and 95% Ranges

Writing Score and Writing Elo. The Writing Score (0 to 100) is the weighted average of the nine metric scores: seven from the judges, Length Adherence from code and the Slop Score half from each. The Writing Elo is a rating from pairwise comparisons: on each script, each configuration's average across its drafts is compared with every other configuration's, and gaps within the draft-to-draft variation count as draws. Elo rewards winning often, so the two can put configurations in a different order.

Elo ranges. Each 95% range shows how far a configuration's Elo could move if the drafts had come out slightly differently. It comes from resampling every configuration's recorded draft scores on each reference script and ranking again. Comparing two separate ranges does not test the Elo gap between them: ranges far apart are strong evidence for the order, and overlapping ranges do not mean a tie. The reference scripts stay fixed, so the ranges say nothing about new scripts. The methodology page has the full description.

All Thinking Levels of Both Models

Every ranked configuration of GPT-6.1 Sol and Muse Wonder, scored on the same 10 scripts by the same four judges.

How to Read the Chart
  • Each row is one configuration: the model at one thinking level. The dot is its Writing Elo, a rating from pairwise comparisons of the scores on each script, and the bar is its 95% range: how far that Elo could move if the drafts had come out slightly differently.
  • When two bars overlap, the board cannot order those two configurations. Bars far apart are strong evidence for the order.
  • The table under the chart lists the same configurations in the same order and adds the Writing Score (the 0 to 100 consensus of the judges and code), cost, time and configuration rank (the place among all configurations on the board).
GPT-6.1 SolMuse Wonder
ConfigurationWriting Elo95% RangeWriting ScoreCost / ScriptTime / ScriptReasoning TokensConfiguration Rank
GPT-6.1 Sol (max)22042171 to 224082.4$0.23910.2 minN/A#16
GPT-6.1 Sol (xhigh)22022161 to 224582.4$0.1997.8 minN/A#18
GPT-6.1 Sol (low)20842052 to 211681.4$0.0521.5 minN/A#24
GPT-6.1 Sol (high)20422006 to 207781.1$0.0943.3 minN/A#26
GPT-6.1 Sol (medium)20241987 to 205881.0$0.0541.6 minN/A#29
Muse Wonder (max)20051959 to 204480.6$0.3092.0 min9,601#31
Muse Wonder (high)16641600 to 172476.7$0.1490.9 min1,385#58
Muse Wonder (adaptive)16041550 to 166176.2$0.1390.8 min766#70

Cost is one script at the API list price of the route used, uncached and without judging. Time is the average for one accepted script, retries included. N/A under Reasoning Tokens means the board has no separate reasoning count for that route.

Computed Findings Across Thinking Levels

Each finding is computed from the configurations above. Where two 95% ranges overlap, the board cannot order those two configurations.

Writing Elo at Each Shared Level Name

LevelGPT-6.1 SolMuse WonderGap95% Ranges
high20421664+378Separate
max22042005+199Separate

Gap is GPT-6.1 Sol minus Muse Wonder at the same level name, using each model's highest-rated configuration at that level.

Two Chosen Configurations Compared

Pick one configuration of each model to compare their metric scores, consistency across drafts and per-script scores. Each menu starts on the model's best configuration.

Scores by Metric

GPT-6.1 Sol (max)Muse Wonder (max)Solid bar: higher score in that row

GPT-6.1 Sol (max) scores higher on seven of the nine metrics and Muse Wonder (max) on two. Weighted by each metric's share of the Writing Score, Length Adherence does the most to put GPT-6.1 Sol (max) ahead, with a 15.5-point lead on that metric. The weight beside each metric is its share of the Writing Score.

Tone & Voice Match19% weight
78.1
76.7
Writing Craft & Clarity13% weight
78.1
76.6
Substance, Accuracy & Value15% weight
87.3
86.8
Continuity & Emotion14% weight
79.2
81.5
YouTube Best Practices12% weight
78.6
79.3
Hook Strength10% weight
82.8
81.8
Length Adherence8% weight
98.0
82.5
Slop Score5% weight
88.2
84.0
Visual Cue Quality4% weight
83.0
78.4

Consistency Across Drafts

GPT-6.1 Sol (max)Muse Wonder (max)
Score spread across drafts (±)1.401.91
Lowest script score80.6 Script 1078.2 Script 10
Highest script score85.0 Script 982.2 Script 5
Range across scripts4.44.0

Spread is how much the Writing Score moves between a configuration's drafts, and lower is steadier. Green marks the better number in each row.

Scores by Script

Writing Score on each reference script. Gap is GPT-6.1 Sol (max) minus Muse Wonder (max), and the higher score is in bold.

ScriptGPT-6.1 Sol (max)Muse Wonder (max)Gap
Script 1 opinion / warning explainer81.781.3+0.4
Script 2 news-analysis / skeptical explainer82.581.7+0.8
Script 3 personal roadmap / opinion83.681.3+2.3
Script 4 short explainer82.579.5+3.0
Script 5 news-analysis / opinion explainer82.082.2-0.2
Script 6 founder announcement / personal origin story83.381.3+2.0
Script 7 personal technical walkthrough / agentic workflow case study82.278.5+3.7
Script 8 product release announcement / personal observation81.082.1-1.1
Script 9 career guide / hiring analysis85.079.9+5.1
Script 10 engineering process walkthrough / presentation adaptation80.678.2+2.4

Compare With Another Model

Pick a second model. A pair with its own written match-up opens that page, and any other pair opens in the comparison tool.

Nearby Match-Ups by Best Writing Elo

Every configuration wrote five drafts for each of the same 10 briefs, from the same prompt. Generation was closed-book, with the prompt as the only source and no web search or other tools. Each judge scores every draft once: Claude 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, a typed judge from TypeSafe that answers each metric as a multiple-choice question. The channel's finished script is their reference for the voice, and it gets no score on the board itself.

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