FireWorldBench - Temporal Evolution Forecasting (Structured Records): leaderboard
The temporal evolution forecasting dimension of FireWorldBench (Chen et al., 2026): forecasting how the temperature, smoke, visibility and flow fields of a simulated fire will evolve after an observation cutoff. Observations are given as structured sensor traces and physical records; 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 (%; P1, temporal evolution forecasting items of the controlled-simulation subset; structured-observation track (textual sensor traces and physical records); 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 February 2027. 15 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GPT-5.6 Luna | 66.59 | #117 |
| 2 | Kimi K2 | 61.28 | #435 |
| 3 | Qwen 3.5 Plus (2026-02-15) | 60.77 | #178 |
| 4 | DeepSeek V3.2 | 60.7 | #403 |
| 5 | Gemini 2.5 Flash | 59.92 | #452 |
| 6 | Gemma 3 27B (IT) | 59.04 | #1306 |
| 7 | Qwen 3 32B | 58.3 | #960 |
| 8 | Claude Haiku 4.5 | 56.56 | #568 |
| 9 | Qwen 3 235B A22B | 55.38 | #622 |
| 10 | GLM 4.5 Air | 49.53 | #863 |
| 11 | Qwen 3 Next 80B A3B Instruct | 48.41 | #763 |
| 12 | Llama 3.3 70B Instruct | 47.08 | #1353 |
| 13 | Qwen 3 8B | 46.55 | #1838 |
| 14 | Gemma 3 12B (IT) | 34.67 | #1849 |
| 15 | Llama 3.1 8B Instruct | 31.93 | #4277 |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=fireworldbench-temporal-evolution-forecasting-structured-records · How It Works · Data refreshed daily, snapshot 2026-11-12.