FireWorldBench - Causal Mechanism Attribution (Rendered Images): leaderboard

The causal mechanism attribution dimension of FireWorldBench (Chen et al., 2026): attributing an observed change in a simulated fire to its physical mechanism, such as buoyancy, crossflow or ventilation. Observations are given as physics-rendered field images and 3D scene renderings; the score is completion accuracy in percent, averaged over matched multiple-choice and open-report questions and scored deterministically; higher is better.

Metric: Completion accuracy (%; P4, causal mechanism attribution items of the controlled-simulation subset; image-observation track (physics-rendered field visualizations and 3D scene renderings); each cell is the mean of the matched choice-format score (Jaccard overlap of selected and gold option sets) and open-report score (exact agreement of required structured slots); deterministic evaluator, no LLM judge; failed or unparseable responses score 0). Source: arxiv.org. Saturation forecast: Around 2029. 10 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 2.5 Flash41.12#452
2Qwen 3 VL 32B Instruct36.91#582
3InternVL3-38B35.55#905
4GPT-5.6 Luna34.4#117
5Qwen 3 VL 235B A22B Instruct34.38#521
6Claude Haiku 4.534.03#568
7InternVL3-78B33.42#733
8Qwen 3.5 Plus (2026-02-15)32.75#178
9InternVL3-8B26.59#1695
10Qwen 3 VL 8B Instruct24.8#982

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=fireworldbench-causal-mechanism-attribution-rendered-images · How It Works · Data refreshed daily, snapshot 2026-11-12.