Model Comparison
Too close to call: the best configurations, GLM-5.3 (max) and GPT-6 Astra (max), are 35 Elo apart, and their 95% ranges overlap. Among 78 models, each ranked by its best configuration, GLM-5.3 is #7 and GPT-6 Astra is #11. Cost per script: $0.240 for GLM-5.3 (max) and $1.15 for GPT-6 Astra (max).
Last updated , from board data generated at 01:13 UTC.
PickGLM-5.3
GLM-5.3 (max)
Pick GLM-5.3 (max) as the default, since Astra's best costs about 4.8 times as much with no gap the board can measure.
PickGPT-6 Astra
GPT-6 Astra (max)
Pick GPT-6 Astra (max) for research-heavy scripts at $1.15 each, since its 87.5 on Substance, Accuracy & Value is the highest on this page.
Price decides this one for me, and it favors GLM-5.3. GLM-5.3 is the #7 model of 78 and GPT-6 Astra the #11 model, each ranked by its best setting. GLM-5.3 (max) sits 35 Elo above GPT-6 Astra (max), their 95% ranges overlap, and their Writing Scores are a tenth apart, so the board can't separate them on writing. GLM costs $0.240 a script and takes about six minutes. Astra at max costs $1.15, about 4.8 times as much, and takes about nine. The cheaper Astra setting doesn't rescue it. GPT-6 Astra (medium) costs a little more than GLM and trails it by 217 Elo with separate ranges, though it does finish in under two minutes. Thinking does a lot for Astra, 182 Elo from medium to max, and that whole gain lifts it just inside GLM's range. The two write differently. Astra carries about four more points of substance, and its slop score is about five points cleaner. GLM leads on tone, continuity and YouTube structure. So GLM-5.3 is my default, and I'd pay for Astra at max only when factual density matters more than cost.
Disclosure: GLM-5.3 and GPT-6 Astra each come from the same lab as one of the judges (GLM 5.3 Flash and GPT-6.1 Sol). Neither is 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 GLM-5.3 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 |
|---|---|---|---|---|---|---|---|
| GLM-5.3 (max) | 2220 | 2183 to 2259 | 82.4 | $0.240 | 6.1 min | 46,444 | #15 |
| 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 |
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.
GLM-5.3 (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, YouTube Best Practices does the most to put GLM-5.3 (max) ahead, with a 5.1-point lead on that metric. The weight beside each metric is its share of the Writing Score.
| GLM-5.3 (max) | GPT-6 Astra (max) | |
|---|---|---|
| Score spread across drafts (±) | 1.39 | 1.87 |
| Lowest script score | 80.5 Script 10 | 80.6 Script 1 |
| Highest script score | 84.1 Script 7 | 85.8 Script 9 |
| Range across scripts | 3.6 | 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 GLM-5.3 (max) minus GPT-6 Astra (max), and the higher score is in bold.
| Script | GLM-5.3 (max) | GPT-6 Astra (max) | Gap |
|---|---|---|---|
| Script 1 opinion / warning explainer | 82.1 | 80.6 | +1.5 |
| Script 2 news-analysis / skeptical explainer | 82.5 | 82.0 | +0.5 |
| Script 3 personal roadmap / opinion | 81.5 | 84.3 | -2.8 |
| Script 4 short explainer | 81.0 | 82.7 | -1.7 |
| Script 5 news-analysis / opinion explainer | 82.5 | 81.3 | +1.2 |
| Script 6 founder announcement / personal origin story | 82.9 | 83.6 | -0.7 |
| Script 7 personal technical walkthrough / agentic workflow case study | 84.1 | 81.6 | +2.5 |
| Script 8 product release announcement / personal observation | 82.7 | 80.6 | +2.1 |
| Script 9 career guide / hiring analysis | 84.0 | 85.8 | -1.8 |
| Script 10 engineering process walkthrough / presentation adaptation | 80.5 | 80.7 | -0.2 |
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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