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# Gemini Robotics Embodied Reasoning 2 is now available on Google Cloud

**[Google Cloud](https://daily.dev/sources/gcp)** · 7 min read · 0 upvotes · 0 comments

## Summary

Google Cloud has launched Gemini Robotics Embodied Reasoning 2 (ER 2) in public preview on the Gemini platform. The model acts as a robot's high-level reasoning layer, combining spatial-temporal video understanding with long-horizon planning across any robot embodiment, from stationary arms to humanoids. It pinpoints critical events in video, such as when to stop pouring a liquid, with 91.3% accuracy and a 0.96-second mean absolute frame distance, running at 4x the execution speed and a fraction of the compute cost of many larger model categories. It can also read values across over 10 instrument types like dials and digital displays. Developers can simulate in MuJoCo-Warp or NVIDIA Isaac Sim, train custom VLA models, and deploy via Google Distributed Cloud and GKE. Boston Dynamics, Arm, DeepReach, and A*STAR IMRE are quoted as customers building with the model.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://cloud.google.com/blog/products/ai-machine-learning/gemini-robotics-embodied-reasoning-2-is-now-available-on-google-cloud>

## Questions this post answers

### What is Gemini Robotics ER 2 and what does it do for robots?

Gemini Robotics ER 2 is a specialized Gemini model that acts as a robot's high-level reasoning brain, combining spatial and temporal video understanding with long-horizon planning. It lets robots converse naturally, orchestrate low-level action models and hardware APIs, execute multi-minute tasks with hundreds of decisions, and collaborate across multi-robot teams, working across embodiments from stationary arms to humanoids.

_Teams evaluating physical AI stacks can track robotics model releases like this one on daily.dev._

### How accurate is Gemini Robotics ER 2 at detecting critical events in video for robot tasks?

It pinpoints the exact video frame where a critical event occurs, such as when to stop pouring a liquid, with 91.3% accuracy and a 0.96-second mean absolute frame distance. It runs at 4 times the execution speed and a fraction of the compute cost of many larger model categories, while also reading over 10 instrument categories like dials, sight glasses, and digital displays.

_Developers comparing physical AI models on accuracy and cost follow benchmark details like these on daily.dev._

### What tools can I use to simulate and train robots with Gemini Robotics ER 2 on Google Cloud?

Robot behaviors can be tested before touching hardware using MuJoCo-Warp and NVIDIA Isaac Sim simulations, with synthetic scenario generation and workcell imagery auto-labeling on the Gemini platform. Demonstration videos can be curated and labeled using spatial pointing, moment finding, and progress classification, then used to train custom Vision-Language-Action models via the Gemini platform, GKE, or Cluster Director.

_Engineers planning a robotics simulation and training pipeline keep up with platform options like this on daily.dev._

## Similar posts on daily.dev

- [Google releases Gemini 3 Flash, enabling faster, more cost effective reasoning](https://daily.dev/posts/google-releases-gemini-3-flash-enabling-faster-more-cost-effective-reasoning-1y9yu2yfb) · SD Times · 0 upvotes · 0 comments

---

Tags: [#gcp](https://daily.dev/tags/gcp), [#robotics](https://daily.dev/tags/robotics)

[View this post on daily.dev](https://daily.dev/posts/gemini-robotics-embodied-reasoning-2-is-now-available-on-google-cloud-6zayfgcj0)

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