Model Comparison
GPT-5.6 Terra (ultra) leads GPT-5.6 Luna (ultra) by 262 Elo, and their 95% ranges sit 177 Elo apart. Even GPT-5.6 Terra's lowest-rated configuration, GPT-5.6 Terra (medium), ranks above GPT-5.6 Luna (ultra). Among 78 models, each ranked by its best configuration, GPT-5.6 Terra is #13 and GPT-5.6 Luna is #24. Cost per script: $0.275 for GPT-5.6 Terra (ultra) and $0.026 for GPT-5.6 Luna (ultra).
Last updated , from board data generated at 01:13 UTC.
PickGPT-5.6 Terra
GPT-5.6 Terra (medium)
Pick GPT-5.6 Terra (medium) for the script, since at $0.062 it sits 186 Elo above GPT-5.6 Luna (ultra) and comes back in half the time.
PickGPT-5.6 Luna
GPT-5.6 Luna (ultra)
Pick GPT-5.6 Luna (ultra) when the bill matters more than the voice, at $0.026 a script against $0.062 for GPT-5.6 Terra (medium).
More thinking pays off very differently for these two models, and that decides how I'd use each. GPT-5.6 Terra moves less. GPT-5.6 Terra (ultra) is 76 Elo above GPT-5.6 Terra (medium), their 95% ranges overlap so the board can't separate them, and ultra costs more than four times as much. GPT-5.6 Luna needs the extra thinking: its ultra setting is 203 Elo above medium, where Length Adherence falls to 70.9. Between the two models, the #13 model of 78 and the #24 model when each is ranked by its best setting, Terra leads at both shared level names. Even Terra at medium, in half the time, sits 186 Elo above GPT-5.6 Luna (ultra), with ranges that don't overlap, which is strong evidence for that order. Luna at ultra has its case. It costs $0.026 a script against $0.062 for Terra at medium, with better length and slightly better visual cues. It loses me on tone, almost seven points back. Terra at medium is my pick for the script, and I'd keep Luna at ultra for cheap first drafts.
Disclosure: both models come from the same lab as one of the four judges, GPT-6.1 Sol. The other judges sit outside that lab, so 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 GPT-5.6 Terra and GPT-5.6 Luna, 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 | Configuration Rank |
|---|---|---|---|---|---|---|
| GPT-5.6 Terra (ultra) | 2074 | 2035 to 2113 | 81.4 | $0.275 | 8.0 min | #25 |
| GPT-5.6 Terra (medium) | 1998 | 1952 to 2041 | 80.7 | $0.062 | 1.4 min | #33 |
| GPT-5.6 Luna (ultra) | 1812 | 1768 to 1858 | 78.8 | $0.026 | 3.1 min | #49 |
| GPT-5.6 Luna (medium) | 1609 | 1572 to 1647 | 76.7 | $0.0065 | 0.5 min | #66 |
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.
Each finding is computed from the configurations above. Where two 95% ranges overlap, the board cannot order those two configurations.
| Level | GPT-5.6 Terra | GPT-5.6 Luna | Gap | 95% Ranges |
|---|---|---|---|---|
| medium | 1998 | 1609 | +389 | Separate |
| ultra | 2074 | 1812 | +262 | Separate |
Gap is GPT-5.6 Terra minus GPT-5.6 Luna at the same level name, using each model's highest-rated configuration at that level.
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.
GPT-5.6 Terra (ultra) scores higher on all nine metrics. Weighted by each metric's share of the Writing Score, Tone & Voice Match does the most to put GPT-5.6 Terra (ultra) ahead, with a 5.0-point lead on that metric. The weight beside each metric is its share of the Writing Score.
| GPT-5.6 Terra (ultra) | GPT-5.6 Luna (ultra) | |
|---|---|---|
| Score spread across drafts (±) | 1.38 | 2.07 |
| Lowest script score | 79.8 Script 4 | 76.0 Script 7 |
| Highest script score | 83.0 Script 6 | 80.8 Script 9 |
| Range across scripts | 3.2 | 4.8 |
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 GPT-5.6 Terra (ultra) minus GPT-5.6 Luna (ultra), and the higher score is in bold.
| Script | GPT-5.6 Terra (ultra) | GPT-5.6 Luna (ultra) | Gap |
|---|---|---|---|
| Script 1 opinion / warning explainer | 81.1 | 78.5 | +2.6 |
| Script 2 news-analysis / skeptical explainer | 82.1 | 80.3 | +1.8 |
| Script 3 personal roadmap / opinion | 82.5 | 79.7 | +2.8 |
| Script 4 short explainer | 79.8 | 77.4 | +2.4 |
| Script 5 news-analysis / opinion explainer | 82.2 | 79.7 | +2.5 |
| Script 6 founder announcement / personal origin story | 83.0 | 80.6 | +2.4 |
| Script 7 personal technical walkthrough / agentic workflow case study | 80.6 | 76.0 | +4.6 |
| Script 8 product release announcement / personal observation | 80.3 | 78.4 | +1.9 |
| Script 9 career guide / hiring analysis | 81.8 | 80.8 | +1.0 |
| Script 10 engineering process walkthrough / presentation adaptation | 80.6 | 76.9 | +3.7 |
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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