CapRL++ Prism - MVBench: leaderboard

CapRL++ (arXiv 2606.09393v1) Table 6 measures video captioners by caption utility: each model captions the video, then "a text-only LLM answers task-specific questions based solely on the generated caption", with the answering LLM fixed "to a fine-tuned Qwen2.5-3B-Instruct". The score shows how much answerable information a caption carries, not native video QA; all Qwen3-VL rows are Instruct variants and the frame count is not stated. Questions from MVBench. Metric: Accuracy (%).

Metric: MVBench accuracy (%) answered from the model's caption (Prism caption-utility protocol: the listed model captions each video, then a fixed text-only answering LLM (a fine-tuned Qwen2.5-3B-Instruct) answers the benchmark's questions from the caption alone; all Qwen3-VL models are Instruct variants; frame count not stated). Source: arxiv.org. Saturation forecast: Around February 2027. 6 models tracked.

Top models

#ModelScoreOverall rank
1Qwen 3 VL 32B Instruct60.5#291
2Qwen 3 VL 235B A22B Instruct59.5#281
3Qwen 3 VL 8B Instruct58.3#420
4Qwen 3 VL 4B Instruct56.8#502

No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #6 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=caprl-plus-plus-prism-mvbench · How It Works · Data refreshed daily, snapshot 2026-11-06.