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Kimi K3 (thinking) vs GLM-5

Should you write with Kimi K3 (thinking) or GLM-5? 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 (thinking) leads overall, 87.2 to 82.8.

Kimi K3 (thinking)
#41 Elo 2098 · 87.2/100
GLM-5
#66 Elo 1692 · 82.8/100
Cost / script
$0.095 vs $0.050
Human baseline
90.9 Kimi K3 (thinking) falls below it · GLM-5 falls below it

The verdict

Between these two open-weights models, Kimi K3 (thinking) is the one to run. It's #41 to GLM-5's #66, roughly four hundred Elo ahead, and it wins all nine metrics. Length Adherence is where GLM-5 falls furthest behind, close to eight points, with continuity next. Kimi is also faster, a little over a minute per script against about three. GLM-5 costs about $0.050 a script against $0.095, roughly half. That's the only argument for it, and if you're set on GLM, GLM-5.3 ranks far above both of these anyway.

Pick Kimi K3 (thinking) when you want fast, on-length open-weights scripts.
Pick GLM-5 only when halving the cost matters more than the quality drop.

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 (thinking), orange is GLM-5, 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, Continuity & Emotion does the most to put Kimi K3 (thinking) ahead: it leads there by 6.2 points. If you care about one thing, say voice or length, go straight to that row.

Tone & Voice Match19% weight
87.3
83.2
Writing Craft & Clarity13% weight
88.3
83.7
Substance, Accuracy & Value15% weight
87.1
83.4
Continuity & Emotion14% weight
86.4
80.2
YouTube Best Practices12% weight
86.8
83.1
Hook Strength10% weight
88.3
85.6
Length Adherence8% weight
86.3
78.5
Slop Score (EQ-Bench + ours)5% weight
89.8
87.6
Visual Cue Quality4% weight
83.5
79.8

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 (thinking) costs about 1.9x as much per script as GLM-5.

Kimi K3 (thinking)GLM-5
Overall / 10087.282.8
Writing Elo20981692
Score spread across drafts (± overall std)1.5502.400
Cost per script (USD)0.0950.050
Avg time per script (min)1.23.1
Open weightsYesYes

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 (thinking) · GLM-5. The whole scoring pipeline is on the methodology page.

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