Kimi K3 vs GPT-5.6 Sol (high)
Should you write with Kimi K3 or GPT-5.6 Sol (high)? On this page the only thing that changes is the model. Both wrote their own version of the scripts behind 10 of my What's AI videos, five drafts per script, and three judges from three model families scored every draft blind, with my finished script as the reference. Kimi K3 leads overall, 88.5 to 87.6. Heads-up: GPT-5.6 Sol (high) shares its model line with one of the three judges. The panel spans three model families, so no model here is scored by its own family alone (how the panel works).
The verdict
Kimi K3 is the better writer here, though the margin is modest. It's #21 against #33, about 83 Elo ahead, and the Elo ranges only just miss each other, so I'd call it a lean rather than a sure thing. Kimi's lead is on the hook and YouTube structure, a couple of points each. GPT-5.6 Sol (high) answers with sharper visual cues, a cleaner Slop Score and slightly more substance. It's also cheaper at about $0.155 against $0.260, and much faster, under a minute and a half per script against about four. Kimi is open weights; GPT-5.6 Sol (high) isn't. If turnaround matters more than a slightly stronger hook, GPT is a fine choice.
Pick Kimi K3 when the hook and the YouTube structure of the script are what you're paying for.
Pick GPT-5.6 Sol (high) when you want fast, clean drafts with strong visual cues at a lower price.
How to read these numbers
Overall vs Elo. Overall is the weighted rubric score. Elo compares each model's five-draft average with every other model's, script by script, and counts gaps inside run-to-run noise as draws, so it rewards winning often and can disagree with overall. My own scripts score 90.9 on the same rubric, not a literal 100. Right now 2 of 167 ranked configurations reach it. A model above that line writes at that level on this rubric. That's not the same as beating my script line for line.
Reading the Elo intervals. Each 95% range comes from resampling every model's recorded run scores on each task and re-ranking. Comparing these separate ranges does not test the Elo gap between two models: far apart is strong evidence, and overlap isn't a tie. The tasks stay fixed, so the ranges say nothing about new tasks (the long version).
Metric by metric: where the gap comes from
Blue is Kimi K3, orange is GPT-5.6 Sol (high), and the solid bar takes the metric. The weight under each name is how much it counts toward the overall. Weighted by how much each metric counts, Tone & Voice Match does the most to put Kimi K3 ahead: it leads there by 1.9 points. If you care about one thing, say voice or length, go straight to that row.
Cost, speed, and consistency
Quality is half the decision. The other half is what each script costs you, how long you wait, and how often you get a bad draft. The lead has a price: Kimi K3 costs about 1.7x as much per script as GPT-5.6 Sol (high).
| Kimi K3 | GPT-5.6 Sol (high) | |
|---|---|---|
| Overall / 100 | 88.5 | 87.6 |
| Writing Elo | 2217 | 2134 |
| Score spread across drafts (± overall std) | 1.260 | 1.330 |
| Cost per script (USD) | 0.260 | 0.155 |
| Avg time per script (min) | 3.9 | 1.4 |
| Open weights | Yes | No |
Green wins the row, and for spread, cost and time, lower wins. Cost is one script at recorded list prices, uncached and without judging, so your real bill will differ. Spread is how much the overall score moves across a model's drafts, and time is the average time to get one accepted script, retries included.
Want the script-by-script detail? Full scorecards: Kimi K3 · GPT-5.6 Sol (high). The whole scoring pipeline is on the methodology page.
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