Model Comparison
Kimi K3.1 Pro (max) leads DeepSeek V4.1 Flash 1017 (max) by 122 Elo, and their 95% ranges sit 37 Elo apart. Among 83 models, each ranked by its best configuration, Kimi K3.1 Pro is #7 and DeepSeek V4.1 Flash 1017 is #14. Cost per script: $0.251 for Kimi K3.1 Pro (max) and $0.014 for DeepSeek V4.1 Flash 1017 (max).
Last updated , from board data generated at 22:06 UTC.
Ranks in the picks and verdict are configuration ranks: each setting's place among all 136 configurations. The cards above give each model's rank.
PickKimi K3.1 Pro
Kimi K3.1 Pro (max)
Pick Kimi K3.1 Pro (max) for a final script where visual cues and substance carry the video, since it leads DeepSeek's best there by 9.6 and 5.9 points, at $0.251 a script.
PickDeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 (max)
Pick DeepSeek V4.1 Flash 1017 (max) as the everyday drafter at $0.014 a script, since it edges Kimi on tone and craft.
Kimi K3.1 Pro rates higher, and DeepSeek V4.1 Flash 1017 sounds a little more like me. Kimi K3.1 Pro (max) leads DeepSeek V4.1 Flash 1017 (max) by 122 Elo with separate 95% ranges, #14 on the board against #25, and wins seven of the ten scripts. By best configuration, that's the #7 model of 83 against the #14 model. DeepSeek is about two points ahead on tone and almost two on craft. Kimi wins on content: almost ten points on visual cues, about six on substance and a stronger hook. Then the bill. DeepSeek costs $0.014 and 1.3 minutes a script, Kimi $0.251 and 5.5 minutes, about 18 times as much. DeepSeek's thinking level barely matters, 44 Elo from high to max, so its high setting at under a cent is a fine draft too. For a final script where the visuals and the facts carry the video, I'd pay for Kimi. Day to day, I'd draft on DeepSeek.
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 K3.1 Pro and DeepSeek V4.1 Flash 1017, 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 K3.1 Pro (max) | 2205 | 2166 to 2246 | 82.5 | $0.251 | 5.5 min | 19,487 | #14 |
| DeepSeek V4.1 Flash 1017 (max) | 2083 | 2041 to 2129 | 81.6 | $0.014 | 1.3 min | 16,960 | #25 |
| DeepSeek V4.1 Flash 1017 (high) | 2039 | 1990 to 2085 | 81.1 | $0.0095 | 0.9 min | 9,728 | #28 |
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.
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 K3.1 Pro (max) 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 Kimi K3.1 Pro (max) ahead, with a 5.9-point lead on that metric. The weight beside each metric is its share of the Writing Score.
| Kimi K3.1 Pro (max) | DeepSeek V4.1 Flash 1017 (max) | |
|---|---|---|
| Score spread across drafts (±) | 1.65 | 1.58 |
| Lowest script score | 80.4 Script 7 | 79.9 Script 4 |
| Highest script score | 85.5 Script 9 | 83.0 Script 7 |
| Range across scripts | 5.1 | 3.1 |
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.
Writing Score on each reference script. Gap is Kimi K3.1 Pro (max) minus DeepSeek V4.1 Flash 1017 (max), and the higher score is in bold.
| Script | Kimi K3.1 Pro (max) | DeepSeek V4.1 Flash 1017 (max) | Gap |
|---|---|---|---|
| Script 1 opinion / warning explainer | 81.3 | 80.5 | +0.8 |
| Script 2 news-analysis / skeptical explainer | 83.2 | 80.8 | +2.4 |
| Script 3 personal roadmap / opinion | 81.9 | 80.5 | +1.4 |
| Script 4 short explainer | 82.0 | 79.9 | +2.1 |
| Script 5 news-analysis / opinion explainer | 84.2 | 82.9 | +1.3 |
| Script 6 founder announcement / personal origin story | 83.0 | 81.2 | +1.8 |
| Script 7 personal technical walkthrough / agentic workflow case study | 80.4 | 83.0 | -2.6 |
| Script 8 product release announcement / personal observation | 82.1 | 82.6 | -0.5 |
| Script 9 career guide / hiring analysis | 85.5 | 83.0 | +2.5 |
| Script 10 engineering process walkthrough / presentation adaptation | 81.3 | 81.6 | -0.3 |
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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