CCR-Bench - Content Elements: leaderboard

Metric: Soft satisfaction rate (0-1, times 100) of the content-element constraints (expressive techniques, content source, specific content) on CCR-Bench's 64 complex content-format instructions (2-6 tightly coupled content and format constraints each, built on high-difficulty instructions by Gemini-2.5-Pro and refined by experts), temperature 0, model-plus-rule scoring averaged over 10 assessments; higher is better. Source: arxiv.org. Saturation forecast: Estimated already saturated. 9 models tracked.

Top models

#ModelScoreOverall rank
1DeepSeek R1 052898.9#217
2QwQ-32B96.8#410
3Gemini 2.5 Pro96.6#145
4Qwen 3 32B (Thinking)94#424 (Qwen 3 32B)
5GPT-4.191.3#240
6O3 Mini91.3#266
7DeepSeek V3 (0324)90.8#332
8Qwen 3 32B (Non-reasoning)87.4#424 (Qwen 3 32B)
9Qwen 2.5 72B Instruct80#436

No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #8 Claude Fable 5.1.

Interactive version: theaggregate.ai/benchmark?slug=ccr-bench-content-elements · How It Works · Data refreshed daily, snapshot 2026-10-11.