Datasets:

FINAL-Bench
/

World-Model

	---
	license: apache-2.0
	task_categories:
	- other
	language:
	- en
	- ko
	tags:
	- world-model
	- embodied-ai
	- benchmark
	- agi
	- cognitive-evaluation
	- vidraft
	- prometheus
	- wm-bench
	- final-bench-family
	pretty_name: World Model Bench (WM Bench)
	size_categories:
	- n<1K
	configs:
	- config_name: default
	data_files:
	- split: train
	path: wm_bench.jsonl
	---

	# 🌍 World Model Bench (WM Bench) v1.0

	> Beyond FID — Measuring Intelligence, Not Just Motion

	WM Bench is the world's first benchmark for evaluating the cognitive capabilities of World Models and Embodied AI systems.

	[![Leaderboard](https://img.shields.io/badge/🏆_Leaderboard-WM_Bench_Space-blue)](https://huggingface.co/spaces/FINAL-Bench/worldmodel-bench)
	[![Demo](https://img.shields.io/badge/🌍_Demo-PROMETHEUS_World_Model-green)](https://huggingface.co/spaces/FINAL-Bench/World-Model)
	[![FINAL Bench](https://img.shields.io/badge/📊_FINAL_Bench-Text_AGI-orange)](https://huggingface.co/datasets/VIDraft/FINAL-Bench)
	[![License](https://img.shields.io/badge/License-Apache_2.0-yellow)](LICENSE)

	---

	## 🎯 Why WM Bench?

	Existing world model evaluations focus on:
	- FID / FVD — image and video quality ("Does it look real?")
	- Atari scores — performance in fixed game environments

	*WM Bench measures something different: Does the model think* correctly?**

	\| Existing Benchmarks \| WM Bench \|
	\|---\|---\|
	\| FID: "Does it look real?" \| "Does it understand the scene?" \|
	\| FVD: "Is the video smooth?" \| "Does it predict threats correctly?" \|
	\| Atari: Fixed game environment \| Any environment via JSON input \|
	\| No emotion modeling \| Emotion escalation measurement \|
	\| No memory testing \| Contextual memory utilization \|

	---

	## 📊 Benchmark Structure

	### 3 Pillars · 10 Categories · 100 Scenarios

	```
	WM Score (0 – 1000)
	├── 👁 P1: Perception 250 pts — C01, C02
	├── 🧠 P2: Cognition 450 pts — C03, C04, C05, C06, C07
	└── 🔥 P3: Embodiment 300 pts — C08, C09, C10
	```

	Why Cognition is 45%: Existing world models measure perception and motion — but not judgment. WM Bench is the only benchmark that measures the quality of a model's decisions.

	\| Cat \| Name \| World First? \|
	\|-----\|------\|-------------\|
	\| C01 \| Environmental Awareness \| \|
	\| C02 \| Entity Recognition & Classification \| \|
	\| C03 \| Prediction-Based Reasoning \| ✦ \|
	\| C04 \| Threat-Type Differentiated Response \| ✦ \|
	\| C05 \| Autonomous Emotion Escalation \| ✦✦ \|
	\| C06 \| Contextual Memory Utilization \| ✦ \|
	\| C07 \| Post-Threat Adaptive Recovery \| ✦ \|
	\| C08 \| Motion-Emotion Expression \| ✦ \|
	\| C09 \| Real-Time Cognitive-Action Performance \| \|
	\| C10 \| Body-Swap Extensibility \| ✦✦ \|

	✦ = First defined in this benchmark
	✦✦ = No prior research exists

	### Grade Scale

	\| Grade \| Score \| Label \|
	\|-------\|-------\|-------\|
	\| S \| 900+ \| Superhuman \|
	\| A \| 750+ \| Advanced \|
	\| B \| 600+ \| Baseline \|
	\| C \| 400+ \| Capable \|
	\| D \| 200+ \| Developing \|
	\| F \| <200 \| Failing \|

	---

	## 🔌 How to Participate

	No 3D environment needed. WM Bench evaluates via text I/O only:

	```
	INPUT: scene_context JSON
	OUTPUT: PREDICT: left=danger(wall), right=safe(open), fwd=danger(beast), back=safe
	MOTION: a person sprinting right in desperate terror
	```

	### Participation Tracks

	\| Track \| Description \| Max Score \|
	\|-------\|-------------\|-----------\|
	\| A \| Text-only (API) \| 750 / 1000 \|
	\| B \| Text + performance metrics \| 1000 / 1000 \|
	\| C \| Text + performance + live demo \| 1000 / 1000 + ✓ Verified \|

	### Quick Start

	```bash
	git clone https://huggingface.co/datasets/VIDraft/wm-bench-dataset
	cd wm-bench-dataset

	python example_submission.py \
	--api_url https://api.openai.com/v1/chat/completions \
	--api_key YOUR_KEY \
	--model YOUR_MODEL \
	--output my_submission.json
	```

	Then upload `my_submission.json` to the [WM Bench Leaderboard](https://huggingface.co/spaces/FINAL-Bench/worldmodel-bench).

	---

	## 🏆 Current Leaderboard

	![Leaderboard Overview](l1.png)

	\| Rank \| Model \| Org \| WM Score \| Grade \| Track \|
	\|------\|-------\|-----\|----------\|-------\|-------\|
	\| 1 \| VIDRAFT PROMETHEUS v1.0 \| VIDRAFT \| 726 \| B \| C ✓ \|

	![Leaderboard Detail](l2.png)

	![Leaderboard Score Breakdown](l3.png)

	Submit your model at the [WM Bench Leaderboard](https://huggingface.co/spaces/FINAL-Bench/worldmodel-bench)

	---

	## 🌍 PROMETHEUS World Model — Live Demo

	WM Bench is powered by VIDRAFT PROMETHEUS, the world's first real-time embodied AI that combines FloodDiffusion motion generation with a Kimi K2.5 cognitive brain.

	![PROMETHEUS World Model](s1.png)

	> Perceive → Predict → Decide → Act

	![PROMETHEUS Scene — Castle World](s2.png)

	![PROMETHEUS NPC Interaction](s3.png)

	![PROMETHEUS Brain Dashboard](s4.png)

	🔗 Try it live: [FINAL-Bench/World-Model](https://huggingface.co/spaces/FINAL-Bench/World-Model)

	---

	## 📦 Dataset Files

	```
	wm-bench-dataset/
	├── wm_bench.jsonl # 100 scenarios + ground truth
	├── example_submission.py # Participation template
	├── wm_bench_scoring.py # Scoring engine (fully open)
	├── wm_bench_eval.py # Evaluation runner
	└── README.md
	```

	---

	## 🔬 FINAL Bench Family

	WM Bench is part of the FINAL Bench Family — a suite of AGI evaluation benchmarks by VIDRAFT:

	\| Benchmark \| Measures \| Status \|
	\|-----------\|----------\|--------\|
	\| [FINAL Bench](https://huggingface.co/datasets/VIDraft/FINAL-Bench) \| Text AGI (metacognition) \| 🌟 HF Global Top 5 · 4 press coverages \|
	\| WM Bench \| Embodied AGI (world models) \| 🚀 Live \|

	This model is introduced in [Darwin Family](https://arxiv.org/abs/2605.14386).