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. DeepSeek V4 Pro 0813 (max) leads overall, 84.0 to 82.6.
DeepSeek V4 Pro 0813 (max) has the stronger current result: #40 at 1861.4 Elo and 84.04 overall, compared with Muse Spark 1.3 (thinking) at #49, 1699.2 Elo, and 82.63 overall. Their 95% Elo confidence intervals do not overlap, which supports the directional ordering (1794.00–1932.20 and 1653.10–1736.10). DeepSeek V4 Pro 0813 (max) has its clearest metric edges in Length Adherence (86.24 versus 63.88) and Visual Cue Quality (79.47 versus 75.93). Muse Spark 1.3 (thinking) counters on YouTube Best Practices (83.72 versus 81.13) and Continuity & Emotion (82.41 versus 80.77). At the measured run mix, DeepSeek V4 Pro 0813 (max) costs $0.022 per article versus $0.041 for Muse Spark 1.3 (thinking); DeepSeek V4 Pro 0813 (max) is the cheaper route. DeepSeek V4 Pro 0813 (max) is the open-weights option; Muse Spark 1.3 (thinking) is closed. On the current automated evidence, DeepSeek V4 Pro 0813 (max) is the stronger default; Muse Spark 1.3 (thinking) remains a defensible choice when its specific strengths, price, or deployment profile matter more than the headline rank.
Pick DeepSeek V4 Pro 0813 (max) when you prioritize the stronger current board result, length adherence, visual cue quality, open weights, and lower measured cost.
Pick Muse Spark 1.3 (thinking) when you prioritize youtube best practices, and continuity & emotion.
Blue bars: DeepSeek V4 Pro 0813 (max). Orange bars: Muse Spark 1.3 (thinking). Same 0–100 scale; the bold bar wins that metric.
| DeepSeek V4 Pro 0813 (max) | Muse Spark 1.3 (thinking) | |
|---|---|---|
| Overall / 100 | 84.0 | 82.6 |
| Writing Elo | 1861 | 1699 |
| Run-to-run spread (± overall std) | 4.370 | 2.770 |
| Cost per script (USD) | 0.022 | 0.041 |
| Avg latency (s) | 195.2 | 78.0 |
| Open weights | Yes | No |
Full scorecards: DeepSeek V4 Pro 0813 (max) · Muse Spark 1.3 (thinking). How scoring works: methodology.
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