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PaLM-E

Embodied multimodal language model connecting vision, language, and robot control at scale.

Official / sourcePaperBack to Model
VLAMultimodalGoogle

Why we recommend it

Landmark embodied multimodal LLM result

Overview

PaLM-E is catalogued on Embodied AI Hub as a curated model for embodied AI builders.

Embodied multimodal language model connecting vision, language, and robot control at scale.

Why it matters: Landmark embodied multimodal LLM result

Use the official repository and docs as the source of truth for install pins, licenses, and hardware requirements.

Who it is for

Researchers, students, and builders comparing open embodied stacks.

Key highlights

  • Embodied multimodal language model connecting vision, language, and robot control at scale.
  • Type: model; categories: model
  • Marked recommended on the hub

When to use

  • You are mapping the open embodied AI landscape
  • You need a starting URL and judgment note before deep-diving

When not to use

  • You need production SLAs or certified industrial support only
  • License or hardware constraints are incompatible with your deployment

Getting started

  1. 1Open the official URL and read README install pins.
  2. 2Skim license and citation requirements.
  3. 3Run the smallest official example before scaling experiments.
  4. 4Cross-link related hub resources (sim / data / policy) for a full stack.

Papers & reading

Caveats & pitfalls

  • Hub cards are curated summaries — always verify upstream docs.
  • Stars and dates drift; treat extra.stars as approximate.

Content reviewed 2026-07-28