ERQA
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
Google DeepMind open-sources ERQA (400 questions) as an open benchmark alongside the Gemini Robotics release.
Gemini 4 Argon scores 87% on ERQA using pure reasoning, outperforming other frontier models.