Head-to-head on the Towards AI writing benchmark: same 10 real YouTube scripts, five runs each, scored blind by a three-family judge panel. GLM-5.3 leads overall, 88.7 to 87.8. Their per-model Elo intervals overlap on this board.
This one is closer than the ranks suggest. GLM-5.3 sits at #15 with 2256.0 Elo and 88.73 overall; Grok 4.7 (high) is at #26 with 2186.4 Elo and 87.79 overall. Their 95% Elo intervals overlap (2220.4 to 2296.8 against 2130.8 to 2232.5), so do not read much into the exact order. Where GLM-5.3 pulls ahead: Length Adherence (90.43 vs 74.12) and Hook Strength (89.10 vs 88.08). Grok 4.7 (high) still wins on Visual Cue Quality (88.85 vs 83.51) and Slop Score (EQ-Bench + ours) (93.30 vs 92.25), so it is not a clean sweep. The trade is price: GLM-5.3 costs about $0.114 per article against $0.311 for Grok 4.7 (high), so you pay less for the higher rank. GLM-5.3 publishes open weights; Grok 4.7 (high) does not. Default to GLM-5.3. Reach for Grok 4.7 (high) when visual cues and slop score matter more to you than the headline rank.
Pick GLM-5.3 for the stronger board result, length adherence, and the hook.
Pick Grok 4.7 (high) for visual cues and slop score.
Reading the Elo intervals. Each range estimates uncertainty around one model's Elo. We repeatedly sample from every model's recorded run scores on each task and recalculate the full ranking. Comparing these separate ranges does not test the Elo gap between two models. The tasks stay fixed, so the ranges do not measure how the ranking would change on new tasks.
Blue bars: GLM-5.3. Orange bars: Grok 4.7 (high). Same 0–100 scale; the bold bar wins that metric.
| GLM-5.3 | Grok 4.7 (high) | |
|---|---|---|
| Overall / 100 | 88.7 | 87.8 |
| Writing Elo | 2256 | 2186 |
| Run-to-run spread (± overall std) | 1.180 | 2.670 |
| Cost per script (USD) | 0.114 | 0.311 |
| Avg latency (s) | 312.8 | 519.0 |
| Open weights | Yes | No |
Full scorecards: GLM-5.3 · Grok 4.7 (high). How scoring works: methodology.
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