Model Comparison
Too close to call: the best configurations, Kimi K3 (max) and GPT-6 Astra (max), are 18 Elo apart, and their 95% ranges overlap. Among 78 models, each ranked by its best configuration, Kimi K3 is #10 and GPT-6 Astra is #11. Cost per script: $0.362 for Kimi K3 (max) and $1.15 for GPT-6 Astra (max).
Last updated , from board data generated at 01:13 UTC.
PickKimi K3
Kimi K3 (max)
Pick Kimi K3 (max) for a script the board can't separate from GPT-6 Astra (max), at $0.362 instead of $1.15.
PickGPT-6 Astra
GPT-6 Astra (max)
Pick GPT-6 Astra (max) when the facts and the exact length matter most, since it leads by four points on substance and scores 98.3 on Length Adherence.
I can't pick a better writer here, and neither can the board. By best setting they're the #10 model and the #11 model of 78. Kimi K3 (max) and GPT-6 Astra (max) are 18 Elo apart with overlapping 95% ranges, the ten scripts split five each, and Astra even has the higher Writing Score by a tenth of a point. So I look at the bill. Both take more than nine minutes, and Kimi does it for $0.362 where Astra asks $1.15, more than three times as much. One rung down, GPT-6 Astra (medium) rates above Kimi K3 (high) at about twice the price, and those ranges overlap too, so the order flips without settling anything. Kimi loses more when you turn its thinking down, 225 Elo against 182 for Astra, so I'd only run Kimi at max. Astra's extra money goes into the facts, four points more on substance at max, plus less slop and length closer to the target. Kimi leads on continuity and YouTube best practices. With prices this far apart, I'd start with Kimi and switch to Astra for fact-heavy scripts.
Disclosure: GPT-6 Astra 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.
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.
Every ranked configuration of Kimi K3 and GPT-6 Astra, scored on the same 10 scripts by the same four judges.
Shaded rows are the configurations chosen for the metric comparison below.
| Configuration | Writing Elo | 95% Range | Writing Score | Cost / Script | Time / Script | Reasoning Tokens | Configuration Rank |
|---|---|---|---|---|---|---|---|
| Kimi K3 (max) | 2203 | 2158 to 2243 | 82.2 | $0.362 | 9.9 min | 18,568 | #20 |
| GPT-6 Astra (max) | 2185 | 2145 to 2223 | 82.3 | $1.15 | 9.2 min | N/A | #21 |
| GPT-6 Astra (medium) | 2003 | 1968 to 2035 | 80.7 | $0.262 | 1.5 min | N/A | #32 |
| Kimi K3 (high) | 1978 | 1936 to 2029 | 80.3 | $0.128 | 2.8 min | 3,081 | #37 |
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.
Each finding is computed from the configurations above. Where two 95% ranges overlap, the board cannot order those two configurations.
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.
Kimi K3 (max) scores higher on five of the nine metrics and GPT-6 Astra (max) on four. Weighted by each metric's share of the Writing Score, Substance, Accuracy & Value does the most to put GPT-6 Astra (max) ahead, with a 4.0-point lead on that metric. The weight beside each metric is its share of the Writing Score.
| Kimi K3 (max) | GPT-6 Astra (max) | |
|---|---|---|
| Score spread across drafts (±) | 1.68 | 1.87 |
| Lowest script score | 80.0 Script 10 | 80.6 Script 1 |
| Highest script score | 83.8 Script 9 | 85.8 Script 9 |
| Range across scripts | 3.8 | 5.2 |
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.
Writing Score on each reference script. Gap is Kimi K3 (max) minus GPT-6 Astra (max), and the higher score is in bold.
| Script | Kimi K3 (max) | GPT-6 Astra (max) | Gap |
|---|---|---|---|
| Script 1 opinion / warning explainer | 81.4 | 80.6 | +0.8 |
| Script 2 news-analysis / skeptical explainer | 82.6 | 82.0 | +0.6 |
| Script 3 personal roadmap / opinion | 81.8 | 84.3 | -2.5 |
| Script 4 short explainer | 80.1 | 82.7 | -2.6 |
| Script 5 news-analysis / opinion explainer | 83.4 | 81.3 | +2.1 |
| Script 6 founder announcement / personal origin story | 83.2 | 83.6 | -0.4 |
| Script 7 personal technical walkthrough / agentic workflow case study | 83.6 | 81.6 | +2.0 |
| Script 8 product release announcement / personal observation | 82.3 | 80.6 | +1.7 |
| Script 9 career guide / hiring analysis | 83.8 | 85.8 | -2.0 |
| Script 10 engineering process walkthrough / presentation adaptation | 80.0 | 80.7 | -0.7 |
Each configuration name in the table above opens its own scorecard.
Pick a second model. A pair with its own written match-up opens that page, and any other pair opens in the comparison tool.
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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