GPT-5.6 Sol (high) vs Qwen3.7 Max (high)
Should you write with GPT-5.6 Sol (high) or Qwen3.7 Max (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. GPT-5.6 Sol (high) leads overall, 87.6 to 80.8. 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
If you're paying per script, Qwen3.7 Max (high) looks tempting at well under half of GPT's price. Then you see the scores. GPT-5.6 Sol (high) sits at #33 against #89 and wins all nine metrics. The widest gap is visual cues, but the two I'd weigh for a script you'll record are substance and voice, where the judges put GPT seven to eight points ahead on both. Qwen's case is $0.055 per script against $0.155. That adds up at volume, sure, but if every Qwen script needs a heavy rewrite, you haven't saved much.
Pick GPT-5.6 Sol (high) for anything that ships: it wins every metric here, with clear leads on substance and voice.
Pick Qwen3.7 Max (high) only for rough internal drafts where cost per script matters more than quality.
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 GPT-5.6 Sol (high), orange is Qwen3.7 Max (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 GPT-5.6 Sol (high) ahead: it leads there by 7.4 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: GPT-5.6 Sol (high) costs about 2.8x as much per script as Qwen3.7 Max (high).
| GPT-5.6 Sol (high) | Qwen3.7 Max (high) | |
|---|---|---|
| Overall / 100 | 87.6 | 80.8 |
| Writing Elo | 2134 | 1525 |
| Score spread across drafts (± overall std) | 1.330 | 2.190 |
| Cost per script (USD) | 0.155 | 0.055 |
| Avg time per script (min) | 1.4 | 1.7 |
| Open weights | No | 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: GPT-5.6 Sol (high) · Qwen3.7 Max (high). The whole scoring pipeline is on the methodology page.
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