# Gemini Robotics ER 2 — the planning brain that watches video and coordinates robots

> DeepMind's embodied-reasoning brain plans multi-step robot work, watches the video, and orchestrates multiple robots at once.

- Org: Google DeepMind
- Date: 2026-07-30
- Category: model
- Source: https://blog.google/innovation-and-ai/models-and-research/google-deepmind/gemini-robotics-er-2/
- Canonical page: https://ai-tldr.dev/releases/google-deepmind-gemini-robotics-er-2/

## In short

Gemini Robotics ER 2 handles high-level reasoning for robots: continuous video, multi-step task planning, tool orchestration, and multi-robot coordination. Hits 91.3% on moment-finding and 57.4% on progress classification.

## What it is

Gemini Robotics ER 2 is Google DeepMind's high-level embodied-reasoning model — the successor to Gemini Robotics-ER 1.6. It chats with humans, understands the physical world, plans multi-step tasks, and orchestrates other tools (including Vision-Language-Action models and APIs) so a robot can carry the plan out.

## How it works

The ER 2 model ingests a continuous video feed alongside language and robot state, then tracks progress across five discrete levels and flags critical moments in the stream (57.4% and 91.3% accuracy respectively in DeepMind's tests). It calls out to a paired VLA — such as Gemini Robotics 2 — to execute low-level motion, and shares a semantic scene understanding so multiple heterogeneous robots can coordinate on the same task.

## Why it matters

Splitting the robot stack into a Gemini Robotics 2 VLA for motion and a Gemini Robotics ER 2 brain for reasoning lets developers upgrade one without retraining the other. The step-change in video understanding also means robots can self-correct mid-task instead of failing quietly, and multi-robot support opens the door to warehouse and home scenarios that need more than one machine cooperating.

## Who it's for

robotics developers building agent stacks on Gemini

## Try it

ai.google.dev/gemini-api/docs/robotics-overview

## Quick facts

- Maker: Google DeepMind
- Role: High-level planning brain paired with Gemini Robotics 2 VLA
- Inputs: Continuous video + language + robot state
- New capabilities: Real-time video understanding, multi-robot coordination, tool orchestration
- Progress classification: 57.4% accuracy across 5 progress levels
- Moment-finding: 91.3% accuracy, 0.96s mean absolute distance
- Availability: Gemini API + Google AI Studio, sample code on GitHub

## FAQ

### How is Gemini Robotics ER 2 different from Gemini Robotics 2?

Gemini Robotics 2 is a Vision-Language-Action (VLA) model that directly moves a humanoid's joints. Gemini Robotics ER 2 sits above it as the embodied-reasoning brain: it plans the multi-step task, watches video for progress, decides which VLA or API to call, and coordinates multiple robots in a shared scene. The two are designed to be paired.

### What does the video understanding actually enable?

Gemini Robotics ER 2 ingests a live video stream and tracks task progress across five discrete levels, hitting 57.4% classification accuracy. It also finds critical moments in the stream with 91.3% accuracy and a mean absolute distance of 0.96 seconds, so the robot can catch a spill, notice a misplaced part, or self-correct mid-task instead of blindly running the plan.

### How do I try Gemini Robotics ER 2 today?

Gemini Robotics ER 2 is exposed through the Gemini API and Google AI Studio, with a robotics-overview page and a Python samples repo at github.com/google-gemini/robotics-samples. Google DeepMind pairs it with the underlying Gemini Robotics 2 VLA for full-body humanoid control shown in the accompanying blog post.

### How does it handle multiple robots?

Gemini Robotics ER 2 lets diverse robots — humanoids, arms, mobile platforms — share a semantic map of the scene and reason jointly about who does what. DeepMind demos two different robots collaborating on the same task without hardcoded coordination rules, using ER 2 as the shared planner.

## Links

- [Announcement](https://blog.google/innovation-and-ai/models-and-research/google-deepmind/gemini-robotics-er-2/)
- [API Docs](https://ai.google.dev/gemini-api/docs/robotics-overview)
- [Samples Repo](https://github.com/google-gemini/robotics-samples)