OpenVLM Video - TempCompass - Caption Matching: leaderboard

TempCompass Caption Matching accuracy from the OpenCompass OpenVLM Video Leaderboard (VLMEvalKit): choosing the caption that matches the video on temporal aspects (action, speed, direction, order, attribute change) that a single frame cannot answer. Accuracy in percent, higher is better; an exact 0, a run with no scorable answers, is left out.

Metric: Accuracy (%). Source: huggingface.co. Saturation forecast: Estimated already saturated. 35 models tracked.

Top models

#ModelScoreOverall rank
1Qwen 2 VL 72B86.36#450
2InternVL3-38B85.83#413
3InternVL3-78B84.5#361
4InternVL2.5-78B83.23#434
5Qwen 2.5 VL 7B80.71#641
6Qwen 2 VL 7B80.37#743
7Qwen2.5-Omni-7B79.51#633
8InternVL3-8B79.04#624
9Claude 3.5 Sonnet78.71#362
10InternVL2-8B76.38#813
11Gemini 1.5 Flash70.66#620
12MiniCPM-V-2.668.53#827
13Phi-4 Multimodal Instruct62.28#922
14Gemini 2.0 Flash16.03#351

No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=openvlm-video-tempcompass-caption-matching · How It Works · Data refreshed daily, snapshot 2026-11-05.