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Evaluation

ERQA

2025ActivePublished: 16 October 2026Updated: 16 October 2026Published
Key innovation
The first open benchmark that isolates the embodied spatial-physical reasoning of multimodal models from robot control — pure visual question answering instead of hardware trials.
Category
Evaluation
Abstraction level
System
Operation level
ModelInference
Use cases
Evaluating embodied reasoning of multimodal modelsMeasuring spatial and physical reasoning in 3DBenchmarking models for robotics applicationsComparing frontier models (e.g. Gemini, GPT)

How it works

ERQA consists of 400 multiple-choice questions combining interleaved images and text. Each question has a single correct answer labelled with a letter (A, B, C, D). A model is given the image(s) and the question and selects an answer; the score is the percentage of correct answers. Questions cover spatial reasoning and world knowledge in real-world scenarios, particularly in a robotics context. The data is distributed as TFRecord examples (features: question, image/encoded, answer, question_type, visual_indices) together with a lightweight evaluation harness for multimodal APIs.

Problem solved

General multimodal benchmarks poorly capture the physical, spatial-world reasoning that robotics requires. ERQA isolates and measures this embodied reasoning independently of controlling a physical robot.

Evolution

Original paper · 2025 · arXiv preprint (Google DeepMind technical report), 2025 · Gemini Robotics Team, Google DeepMind
Gemini Robotics: Bringing AI into the Physical World
Gemini Robotics Team, Google DeepMind
2025
ERQA benchmark released
Inflection point

Google DeepMind open-sources ERQA (400 questions) as an open benchmark alongside the Gemini Robotics release.

2026
Gemini 4 Argon reaches 87% on ERQA

Gemini 4 Argon scores 87% on ERQA using pure reasoning, outperforming other frontier models.