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Model Comparison

GPT-6.1 Sol vs Kimi K3.1 Pro

Overlapping ranges: the best configurations, GPT-6.1 Sol (max) and Kimi K3.1 Pro (max), are 2 Elo apart, and their 95% ranges overlap. Among 84 models, each ranked by its best configuration, GPT-6.1 Sol is #7 and Kimi K3.1 Pro is #8. Cost per script: $0.239 for GPT-6.1 Sol (max) and $0.251 for Kimi K3.1 Pro (max).

Last updated , from board data generated at 20:15 UTC.

GPT-6.1 Sol
2193 Writing Elo of GPT-6.1 Sol (max), its best configuration#7 of 84 models · 82.4/100 Writing Score · $0.239 per script5 configurations on the board
Kimi K3.1 Pro
2191 Writing Elo of Kimi K3.1 Pro (max), its best configuration#8 of 84 models · 82.5/100 Writing Score · $0.251 per script1 configuration on the board

Picks and Verdict

PickGPT-6.1 Sol

GPT-6.1 Sol (xhigh)

Pick GPT-6.1 Sol (xhigh) for less slop and tighter length at $0.199 a script, with an individual Elo range that overlaps Kimi's.

PickKimi K3.1 Pro

Kimi K3.1 Pro (max)

Pick Kimi K3.1 Pro (max) when you want the draft in 5.5 minutes instead of 10.2, with the edge on continuity and visual cues, at $0.251.

The Elo point estimates are close, and speed is the clearest difference. GPT-6.1 Sol is the #7 model of 84 and Kimi K3.1 Pro the #8 model, each ranked by its best setting. At max, the one level name they share, GPT-6.1 Sol (max) sits 2 Elo above Kimi K3.1 Pro (max), the 95% ranges overlap and the ten scripts split five each; that overlap alone does not test their difference. The price is about the same, $0.239 against $0.251, but Sol takes 10.2 minutes where Kimi finishes in 5.5. Sol at xhigh also overlaps Kimi, at $0.199 and 7.8 minutes. Lower down, Sol's ladder is uneven: low rates above high and medium for less money, and going from low to max adds 142 Elo for about 4.6 times the cost. Kimi only runs at max, so I'd hold it against Sol's top two. The metrics split by type. Sol at max has 3.2 points less slop, lands the length 2.6 points closer and scores a little higher on tone. Kimi leads continuity by 1.6, visual cues by 1.9 and YouTube best practices by 1.1. I'd take Sol at xhigh to save a few cents, and Kimi when I want the draft sooner.

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 Kimi K3.1 Pro, 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.
  • Each bar describes one configuration. Overlap alone does not establish a tie or decide their order. Comparing these ranges does not directly test the difference between a pair.
  • 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 SolKimi K3.1 Pro
ConfigurationWriting Elo95% RangeWriting ScoreCost / ScriptTime / ScriptReasoning TokensConfiguration Rank
GPT-6.1 Sol (max)21932151 to 223082.4$0.23910.2 minN/A#13
Kimi K3.1 Pro (max)21912148 to 223182.5$0.2515.5 min19,487#14
GPT-6.1 Sol (xhigh)21652125 to 220282.4$0.1997.8 minN/A#20
GPT-6.1 Sol (low)20512013 to 208381.4$0.0521.5 minN/A#26
GPT-6.1 Sol (high)20131969 to 205681.1$0.0943.3 minN/A#29
GPT-6.1 Sol (medium)19981963 to 202981.0$0.0541.6 minN/A#32

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. The 95% ranges describe individual configurations; overlap alone establishes neither a tie nor an order for a pair.

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)Kimi K3.1 Pro (max)Solid bar: higher score in that row

GPT-6.1 Sol (max) scores higher on four of the nine metrics and Kimi K3.1 Pro (max) on five. Weighted by each metric's share of the Writing Score, Continuity & Emotion does the most to put Kimi K3.1 Pro (max) ahead, with a 1.6-point lead on that metric. The weight beside each metric is its share of the Writing Score.

Tone & Voice Match19% weight
78.1
77.0
Writing Craft & Clarity13% weight
78.1
77.8
Substance, Accuracy & Value15% weight
87.3
88.2
Continuity & Emotion14% weight
79.2
80.8
YouTube Best Practices12% weight
78.6
79.7
Hook Strength10% weight
82.8
83.4
Length Adherence8% weight
98.0
95.4
Slop Score5% weight
88.2
85.0
Visual Cue Quality4% weight
83.0
84.9

Consistency Across Drafts

GPT-6.1 Sol (max)Kimi K3.1 Pro (max)
Score spread across drafts (±)1.401.65
Lowest script score80.6 Script 1080.4 Script 7
Highest script score85.0 Script 985.5 Script 9
Range across scripts4.45.1

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 Kimi K3.1 Pro (max), and the higher score is in bold.

ScriptGPT-6.1 Sol (max)Kimi K3.1 Pro (max)Gap
Script 1 opinion / warning explainer81.781.3+0.4
Script 2 news-analysis / skeptical explainer82.583.2-0.7
Script 3 personal roadmap / opinion83.681.9+1.7
Script 4 short explainer82.582.0+0.5
Script 5 news-analysis / opinion explainer82.084.2-2.2
Script 6 founder announcement / personal origin story83.383.0+0.3
Script 7 personal technical walkthrough / agentic workflow case study82.280.4+1.8
Script 8 product release announcement / personal observation81.082.1-1.1
Script 9 career guide / hiring analysis85.085.5-0.5
Script 10 engineering process walkthrough / presentation adaptation80.681.3-0.7

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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