Benchmark Almanac

ContPhy

Seed2.0 Pro 67.4% leads since February 2026
Fading

Models infer physical properties such as mass and density of fluids and soft bodies from videos and predict their dynamics.

Published at ICML 2024. The format field is a guess.

Released
February 2024
Kind
Physical prediction
Level
Everyday
Scored
Checked automatically
Answers
Multiple choice
Last in a launch post
April 2026, dropped before it saturated
Last model added
June 2026

In the authors’ words

We introduce the Continuum Physical Dataset (ContPhy), a novel benchmark for assessing machine physical commonsense. ContPhy complements existing physical reasoning benchmarks by encompassing the inference of diverse physical properties, such as mass and density, across various scenarios and predicting corresponding dynamics. We evaluated a range of AI models and found that they still struggle to achieve satisfactory performance on ContPhy, which shows that the current AI models still lack physical commonsense for the continuum, especially soft-bodies, and illustrates the value of the proposed dataset. We also introduce an oracle model (ContPRO) that marries the particle-based physical dynamic models with the recent large language models, which enjoy the advantages of both models, precise dynamic predictions, and interpretable reasoning. ContPhy aims to spur progress in perception and reasoning within diverse physical settings, narrowing the divide between human and machine intelligence in understanding the physical world. Project page: https://physical-reasoning-project.github.io

Abstract of ContPhy: Continuum Physical Concept Learning and Reasoning from Videos (arXiv:2402.06119, CC0)
3
Models scored in lab cards
1
Launch post lists it, from 1 lab
2
System cards report it, from 1 lab

Seed2.0 Pro leads with 67.4% among models released by June 2026

Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.

The newest model with a score here came out in June 2026, and nobody has reported a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:

  1. 1 Seed2.0 Pro 67.4%
  2. 2 Seed2.1 Pro 63.6%
  3. 3 Seed2.0 Lite (0428) 62.4%

Source: Labs’ model cards

#ModelScoreSettingDateSource
1 Seed2.0 Pro 67.4% Feb 2026 Lab model card
2 Seed2.1 Pro 63.6% Jun 2026 Lab model card
3 Seed2.0 Lite (0428) 62.4% Apr 2026 Lab model card

Number one over time

Lab claims count from the day the card came out, independent runs from the model’s release.

ByteDance Seed
Lab claims Not tested since Jun 2026
Seed2.0 Pro 67.4%

Source: Labs’ model cards

Scores over time

All the scores we have, one dot each, so a model tested at several settings appears more than once.

Reported by the lab in its model card
0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) Seed2.0 Pro 0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) Seed2.0 Pro

Source: Labs’ model cards

Labs headline it less often now, last in April 2026

Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.

ByteDance Seed
DateLaunch postScoreAs the post writes it
Apr 28, 2026 Seed2.0 Lite (0428) 62.4 ContPhy

2 system cards report it, from 1 lab

Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.

DateDocumentScoreAs the document writes itSection
Jun 23, 2026 Seed2.1 Pro model card 63.6 ContPhy (Table 10) Capabilities
Feb 14, 2026 Seed2.0 Pro model card 67.4 ContPhy (Table 9) Capabilities

More in World models

All 39 in World models
  • AgentWorldBench In use Language world models predict the next environment observation after an agent action, in 7 domains from MCP and search to Android and desktop OS. A judge model scores each prediction against the real observation on five dimensions. GPT-5.4 58.3
  • IntPhys 2 In use Models watch simulated videos and judge whether each event is physically possible, testing object permanence, immutability, continuity and solidity. Scored by accuracy. Muse Spark Open 68.3%
  • QwenWorldBench Fading Models act as world models that simulate agent environments in 7 domains, such as terminal, web, and Android. A rubric judge scores five dimensions. Qwen3.7-Plus 62.1%
  • VPCT Fading Models view an image of a ball, ramps, and three buckets and predict which bucket the ball falls into. Scored by accuracy on 100 problems. Gemini 3 Pro 91%
  • RBench Only in system cards 650 image+text prompts for robot video generation (tasks and embodiments). MLLM judge scores task completion, physical plausibility, stability. Wan 2.6 60.7%
  • PAI-Bench Only in system cards Physical-AI video generation from 1,044 prompts in six domains, VLM-QA plus quality metrics. Companion control and understanding tracks. Cosmos3-Nano 83.7%