FireWorldBench - Physical Field Perception and Grounding (Rendered Images): leaderboard

The physical field perception and grounding dimension of FireWorldBench (Chen et al., 2026): grounding partial observations of a simulated fire in the underlying physical fields, such as locating a source from temperature and soot anomalies. 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 (%; P2, physical field perception and grounding 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 May 2027. 10 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.6 Luna41.11#117
2Gemini 2.5 Flash40.84#452
3Qwen 3.5 Plus (2026-02-15)40.77#178
4Qwen 3 VL 235B A22B Instruct40.42#521
5Qwen 3 VL 32B Instruct40.23#582
6InternVL3-78B37.17#733
7Claude Haiku 4.534.52#568
8InternVL3-38B26.66#905
9InternVL3-8B25.08#1695
10Qwen 3 VL 8B Instruct21.47#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-physical-field-perception-and-grounding-rendered-images · How It Works · Data refreshed daily, snapshot 2026-11-12.