LibreAI / Agentes de IA / Isaac-GR00T
// agents · NVIDIA/Isaac-GR00T

Isaac-GR00T

Isaac-GR00T é um projeto de agentes de IA de código aberto de NVIDIA (NVIDIA/Isaac-GR00T no GitHub). Tem 8.173 estrelas no GitHub e 1.486 forks, é publicado sob a licença Apache-2.0 e foi atualizado pela última vez no GitHub em 7 de outubro de 2026.

NVIDIA Isaac GR00T N1.7 — an open foundation model for generalist robots, ready to fine-tune and deploy.

★ 8,2 mil estrelas⑂ 1,5 mil forksApache-2.0atualizado out 2026
▦ visual: o README deste projeto não inclui nenhuma captura incorporável,
então aqui vai um marcador. O guia abaixo está completo mesmo assim.
// dados do projeto

Dados do projeto

Repositório
NVIDIA/Isaac-GR00T
Estrelas no GitHub
8.173
Forks
1.486
Licença
Apache-2.0
Última atualização no GitHub
7 de outubro de 2026
Categoria
Agentes de IA
Tipo de ficha
Guia de instalação completo
Site oficial
Official site
// como funciona

Como funciona

  1. Clarify your goal

    Check the hardware requirements and your robot/dataset format (LeRobot-style datasets are used in the workflow), and install git-lfs before cloning since demo data uses it.

  2. Get the project

    Clone NVIDIA/Isaac-GR00T from GitHub (or use the install path in the run steps below) and skim its README for the parts relevant to your goal.

  3. Install and configure

    Clone with submodules, install with uv (or the pip alternative), and add the system GL libraries the README lists.

  4. Run your first task

    Run a documented inference or evaluation example with the demo data, then fine-tune on a small slice of your own dataset.

// recursos

Por que as pessoas gostam tanto

Generalist robot foundation model

A pretrained vision-language-action model intended as a base for many robots and tasks, not a single-task policy.

Cosmos-Reason2-2B backbone

N1.7 replaces the older Eagle backbone with Cosmos-Reason2-2B (Qwen3-VL), encoding images at native aspect ratio without padding.

Expanded action space

State and action dimensions expand to 132 with an action horizon of 40, and the flow-matching DiT action head is updated for N1.7.

Multi-dataset fine-tuning

Fine-tune on multiple dataset paths at once with mixture weighting (ds_weights_alpha) for easier multi-source training.

Deployment export

Full-pipeline ONNX and TensorRT export, with hardened policy serving, rollout recording, evaluation and config validation.

Benchmarked openly

Documented results across RoboCasa (including GR1 tabletop tasks), SimplerEnv and real G1 robot evaluation.

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// execute você mesmo

Execute você mesmo

  1. Clone the repository

    Get the source from the official GitHub repository for Isaac-GR00T.

    git clone https://github.com/NVIDIA/Isaac-GR00T.git
    cd Isaac-GR00T
  2. Clone with submodules

    Install git-lfs first (required for the demo data), then clone the repository with its submodules as the README directs.

    sudo apt install git-lfs && git lfs install
    git clone --recurse-submodules https://github.com/NVIDIA/Isaac-GR00T
  3. Install the package

    Install in editable mode with uv (the README's primary path) after cloning; a pip alternative is documented there too.

    uv pip install -e . --verbose  # pip alternative: pip install -e . — see README
// casos de uso

O que você pode criar

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// perguntas frequentes

Perguntas frequentes

Who maintains Isaac-GR00T?

NVIDIA, through the NVIDIA/Isaac-GR00T repository, with the product page at developer.nvidia.com/isaac/gr00t.

Is Isaac-GR00T free to use?

Yes — the project is open source under the Apache-2.0 license as recorded for this listing. See the license terms for any conditions on redistribution.

Does Isaac-GR00T need a paid API key?

The model and code are free under Apache-2.0 with no API key, but you need capable GPU hardware and your own robot demonstration data for meaningful fine-tuning.

How does GR00T compare to training a robot policy from scratch?

Training from scratch needs far more data and compute for basic competence. GR00T starts from a pretrained generalist model you fine-tune — you still need quality demonstrations and GPUs, but the starting point already understands scenes and language.

How do I get started with Isaac-GR00T?

Clone the repository (or use the documented installer), follow the install and configure steps on this page, and run the smallest real task first — run a documented inference or evaluation example with the demo data, then fine-tune on a small slice of your own dataset.

// continue explorando

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// alternativas

Alternativas em Agentes de IA

Os outros projetos de Agentes de IA com mais estrelas no catálogo do LibreAI — a lista realista de alternativas se Isaac-GR00T não for o ideal para você.

// mais em agents

Mais em Agentes de IA

Projetos de Agentes de IA próximos no catálogo, os mais próximos em estrelas de Isaac-GR00T: continue explorando dos dois lados dele.

Baixe o Isaac-GR00T

Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.