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Model Comparison

GPT-5.6 Terra vs GPT-5.6 Luna

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.

GPT-5.6 Terra
2074 Writing Elo of GPT-5.6 Terra (ultra), its best configuration#13 of 78 models · 81.4/100 Writing Score · $0.275 per script2 configurations on the board
GPT-5.6 Luna
1812 Writing Elo of GPT-5.6 Luna (ultra), its best configuration#24 of 78 models · 78.8/100 Writing Score · $0.026 per script2 configurations on the board

Picks and Verdict

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.

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-5.6 Terra and GPT-5.6 Luna, 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-5.6 TerraGPT-5.6 Luna
ConfigurationWriting Elo95% RangeWriting ScoreCost / ScriptTime / ScriptConfiguration Rank
GPT-5.6 Terra (ultra)20742035 to 211381.4$0.2758.0 min#25
GPT-5.6 Terra (medium)19981952 to 204180.7$0.0621.4 min#33
GPT-5.6 Luna (ultra)18121768 to 185878.8$0.0263.1 min#49
GPT-5.6 Luna (medium)16091572 to 164776.7$0.00650.5 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.

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-5.6 TerraGPT-5.6 LunaGap95% Ranges
medium19981609+389Separate
ultra20741812+262Separate

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.

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-5.6 Terra (ultra)GPT-5.6 Luna (ultra)Solid bar: higher score in that row

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.

Tone & Voice Match19% weight
76.9
71.9
Writing Craft & Clarity13% weight
76.8
74.7
Substance, Accuracy & Value15% weight
86.4
84.8
Continuity & Emotion14% weight
80.2
77.2
YouTube Best Practices12% weight
79.3
76.6
Hook Strength10% weight
81.5
80.6
Length Adherence8% weight
93.7
91.8
Slop Score5% weight
84.7
83.9
Visual Cue Quality4% weight
80.3
78.4

Consistency Across Drafts

GPT-5.6 Terra (ultra)GPT-5.6 Luna (ultra)
Score spread across drafts (±)1.382.07
Lowest script score79.8 Script 476.0 Script 7
Highest script score83.0 Script 680.8 Script 9
Range across scripts3.24.8

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.

Scores by Script

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.

ScriptGPT-5.6 Terra (ultra)GPT-5.6 Luna (ultra)Gap
Script 1 opinion / warning explainer81.178.5+2.6
Script 2 news-analysis / skeptical explainer82.180.3+1.8
Script 3 personal roadmap / opinion82.579.7+2.8
Script 4 short explainer79.877.4+2.4
Script 5 news-analysis / opinion explainer82.279.7+2.5
Script 6 founder announcement / personal origin story83.080.6+2.4
Script 7 personal technical walkthrough / agentic workflow case study80.676.0+4.6
Script 8 product release announcement / personal observation80.378.4+1.9
Script 9 career guide / hiring analysis81.880.8+1.0
Script 10 engineering process walkthrough / presentation adaptation80.676.9+3.7

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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