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Model Comparison

GPT-5.6 Sol vs DeepSeek V4.1 Flash 1017

GPT-5.6 Sol (low) leads DeepSeek V4.1 Flash 1017 (max) by 107 Elo, and their 95% ranges sit 16 Elo apart. Even GPT-5.6 Sol's lowest-rated configuration, GPT-5.6 Sol (ultra), ranks above DeepSeek V4.1 Flash 1017 (max). Among 81 models, each ranked by its best configuration, GPT-5.6 Sol is #8 and DeepSeek V4.1 Flash 1017 is #13. Cost per script: $0.113 for GPT-5.6 Sol (low) and $0.014 for DeepSeek V4.1 Flash 1017 (max).

Last updated , from board data generated at 16:59 UTC.

GPT-5.6 Sol
2194 Writing Elo of GPT-5.6 Sol (low), its best configuration#8 of 81 models · 82.3/100 Writing Score · $0.113 per script2 configurations on the board
DeepSeek V4.1 Flash 1017
2087 Writing Elo of DeepSeek V4.1 Flash 1017 (max), its best configuration#13 of 81 models · 81.6/100 Writing Score · $0.014 per script2 configurations on the board

Picks and Verdict

PickGPT-5.6 Sol

GPT-5.6 Sol (low)

Pick GPT-5.6 Sol (low) for scripts you'll publish, since it outranks every DeepSeek configuration at $0.113 and under a minute a script.

PickDeepSeek V4.1 Flash 1017

DeepSeek V4.1 Flash 1017 (max)

Pick DeepSeek V4.1 Flash 1017 (max) for open-weights volume drafting at $0.014 a script, with the closest length on this page.

GPT-5.6 Sol's cheapest configuration is also its best one, and it beats everything DeepSeek V4.1 Flash 1017 has here. GPT-5.6 Sol (low) leads DeepSeek V4.1 Flash 1017 (max) by 107 Elo, with 95% ranges 16 Elo apart, which is strong evidence for that order. That's the #8 model of 81 against the #13 model, each ranked by its best configuration. Sol at low is as fast as DeepSeek at high, 0.9 minutes a script, with the steadiest drafts on this page. Its lead is content: 4.8 points on substance, 4.6 on visual cues and 2.6 on hooks. DeepSeek at max lands 5.1 points closer to the requested length and edges Sol on tone, the heaviest metric. Thinking runs backwards on Sol. GPT-5.6 Sol (ultra) costs about 3.2 times as much, takes 4.1 minutes and lands 12 Elo lower inside overlapping ranges, so I'd never pay for it. DeepSeek's step from high to max goes the other way, 37 Elo for about half a cent. The real trade is $0.113 a script against $0.014, about eight times as much. For a script I'll publish, I'd pay it.

Disclosure: GPT-5.6 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-5.6 Sol and DeepSeek V4.1 Flash 1017, 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 SolDeepSeek V4.1 Flash 1017
ConfigurationWriting Elo95% RangeWriting ScoreCost / ScriptTime / ScriptReasoning TokensConfiguration Rank
GPT-5.6 Sol (low)21942156 to 223282.3$0.1130.9 minN/A#16
GPT-5.6 Sol (ultra)21822143 to 222782.3$0.3674.1 minN/A#19
DeepSeek V4.1 Flash 1017 (max)20872039 to 214081.6$0.0141.3 min16,960#24
DeepSeek V4.1 Flash 1017 (high)20502001 to 209281.1$0.00950.9 min9,728#27

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. Where two 95% ranges overlap, the board cannot order those two configurations.

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 Sol (low)DeepSeek V4.1 Flash 1017 (max)Solid bar: higher score in that row

GPT-5.6 Sol (low) scores higher on five of the nine metrics and DeepSeek V4.1 Flash 1017 (max) on four. Weighted by each metric's share of the Writing Score, Substance, Accuracy & Value does the most to put GPT-5.6 Sol (low) ahead, with a 4.8-point lead on that metric. The weight beside each metric is its share of the Writing Score.

Tone & Voice Match19% weight
78.6
79.2
Writing Craft & Clarity13% weight
79.3
79.5
Substance, Accuracy & Value15% weight
87.1
82.3
Continuity & Emotion14% weight
81.7
81.0
YouTube Best Practices12% weight
79.9
80.1
Hook Strength10% weight
83.7
81.1
Length Adherence8% weight
89.7
94.8
Slop Score5% weight
85.4
84.1
Visual Cue Quality4% weight
79.9
75.3

Consistency Across Drafts

GPT-5.6 Sol (low)DeepSeek V4.1 Flash 1017 (max)
Score spread across drafts (±)1.271.58
Lowest script score79.8 Script 479.9 Script 4
Highest script score84.2 Script 983.0 Script 7
Range across scripts4.43.1

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-5.6 Sol (low) minus DeepSeek V4.1 Flash 1017 (max), and the higher score is in bold.

ScriptGPT-5.6 Sol (low)DeepSeek V4.1 Flash 1017 (max)Gap
Script 1 opinion / warning explainer82.180.5+1.6
Script 2 news-analysis / skeptical explainer82.580.8+1.7
Script 3 personal roadmap / opinion82.380.5+1.8
Script 4 short explainer79.879.9-0.1
Script 5 news-analysis / opinion explainer83.282.9+0.3
Script 6 founder announcement / personal origin story82.881.2+1.6
Script 7 personal technical walkthrough / agentic workflow case study82.083.0-1.0
Script 8 product release announcement / personal observation82.682.60.0
Script 9 career guide / hiring analysis84.283.0+1.2
Script 10 engineering process walkthrough / presentation adaptation82.081.6+0.4

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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