FireWorldBench - Counterfactual Intervention Reasoning (Rendered Images): leaderboard

The counterfactual intervention reasoning dimension of FireWorldBench (Chen et al., 2026): predicting how a simulated fire would respond to an intervention such as a changed opening, exhaust, source or suppression. 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 (%; P5, counterfactual intervention reasoning 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 Flash43.46#452
2InternVL3-78B41.22#733
3Qwen 3.5 Plus (2026-02-15)37.83#178
4Qwen 3 VL 8B Instruct36.42#982
5Qwen 3 VL 32B Instruct35.82#582
6GPT-5.6 Luna34.61#117
7Claude Haiku 4.532.47#568
8InternVL3-38B31.94#905
9InternVL3-8B26.27#1695
10Qwen 3 VL 235B A22B Instruct20.62#521

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

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