VOLTBench - Mean Length Accuracy (200 Sections): leaderboard
Metric: Mean length accuracy (%): 100 x max(0, 1 - |mean output length - target length| / target length) over the five sampled generations per instruction, English simple-difficulty instructions, Story (unstructured) and Code Function (structured) chapter-based tasks, 200-section target; higher is better. Source: arxiv.org. Saturation forecast: Around 2031. 9 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | GPT-4o Mini | 14 |
| 2 | DeepSeek V3 | 3.8 |
| 3 | DeepSeek R1 | 3.4 |
| 4 | Qwen 2.5 7B Instruct | 1.4 |
| 5 | Qwen 2.5 1.5B Instruct | 0.9 |
| 6 | Llama 3.1 8B Instruct | 0.8 |
| 7 | Claude 3.5 Sonnet | 0.5 |
Interactive version: theaggregate.ai/benchmark?slug=voltbench-mean-length-accuracy-200-sections · How It Works · Data refreshed daily, snapshot 2026-10-07.