# Ecosystem, license, and release

> Related Cosmos projects (Framework, Curator, Evaluator), OpenMDW-1.1 license terms, known model limitations, release cadence pointers, and third-party dependency notices.

- Repository: NVIDIA/cosmos
- GitHub: https://github.com/NVIDIA/cosmos
- Human docs: https://grok-wiki.com/public/docs/nvidia-cosmos-82de3e90abd9
- Complete Markdown: https://grok-wiki.com/public/docs/nvidia-cosmos-82de3e90abd9/llms-full.txt

## Source Files

- `README.md`
- `LICENSE`
- `RELEASE.md`
- `cookbooks/cosmos3/README.md`

---

---
title: "Ecosystem, license, and release"
description: "Related Cosmos projects (Framework, Curator, Evaluator), OpenMDW-1.1 license terms, known model limitations, release cadence pointers, and third-party dependency notices."
---

The **NVIDIA/cosmos** repository ships Cosmos 3 cookbooks, benchmarks, and integration quickstarts under **OpenMDW-1.1**, while training, curation, and automated evaluation live in sibling repositories (**cosmos-framework**, **cosmos-curator**, **cosmos-evaluator**). Install paths in this repo pull additional third-party packages (Diffusers, vLLM, vLLM-Omni, `cosmos_guardrail`, Hugging Face tooling); review each dependency’s license before production use.

## Cosmos platform map

NVIDIA Cosmos is an open platform of world models, datasets, and tools for Physical AI (robots, autonomous vehicles, smart infrastructure). This repository focuses on **Cosmos 3** runnable examples and serving guides; the broader platform splits operational concerns across dedicated projects.

```mermaid
flowchart TB
  subgraph cosmos_repo["NVIDIA/cosmos (this repo)"]
    CB["cookbooks/cosmos3"]
    BM["inference_benchmarks.md"]
    QS["README quickstarts"]
  end

  subgraph models["Model artifacts"]
    HF["Hugging Face: nvidia/cosmos3 collection"]
  end

  subgraph framework["cosmos-framework"]
    INF["cosmos_framework.scripts.inference"]
    TRN["Training recipes (Coming Soon)"]
    VLLM3["packages/vllm-cosmos3"]
  end

  subgraph data["cosmos-curator"]
    CUR["Processing, annotation, filtering, deduplication"]
  end

  subgraph eval["cosmos-evaluator"]
    EV["World generation and reasoning evaluation"]
  end

  CB --> INF
  CB --> HF
  QS --> HF
  VLLM3 --> CB
  TRN -.-> CB
  CUR -.-> TRN
  EV -.-> INF
```

| Project | Repository | Role in a Physical AI workflow |
| --- | --- | --- |
| **Cosmos (this repo)** | [NVIDIA/cosmos](https://github.com/NVIDIA/cosmos) | Cosmos 3 cookbooks, `inference_benchmarks.md`, Diffusers/vLLM/vLLM-Omni quickstarts, and example assets |
| **Cosmos Framework** | [NVIDIA/cosmos-framework](https://github.com/NVIDIA/cosmos-framework) | End-to-end setup, native PyTorch inference (`torchrun`), training, and evaluation workflows; hosts `vllm-cosmos3` |
| **Cosmos Curator** | [NVIDIA/cosmos-curator](https://github.com/NVIDIA/cosmos-curator) | Distributed data curation: processing, annotation, filtering, deduplication |
| **Cosmos Evaluator** | [NVIDIA/cosmos-evaluator](https://github.com/NVIDIA/cosmos-evaluator) | Automated evaluation of world generation and world reasoning outputs |

<Info>
Cookbooks that use Cosmos Framework or vLLM require access to `git@github.com:NVIDIA/cosmos-framework.git` (or HTTPS clone). Framework setup is documented in [Cookbook environment setup](/cookbook-environment).
</Info>

### How this repo connects to Framework

| Integration goal | Primary surface in this repo | Where Framework fits |
| --- | --- | --- |
| Generator / Reasoner research with full checkpoint | Diffusers `Cosmos3OmniPipeline` | Optional; Framework exposes `cosmos_framework.scripts.inference` with parallelism presets |
| Production Generator API | vLLM-Omni (`vllm/vllm-omni:cosmos3`) | Same checkpoints; Framework for batch `torchrun` jobs |
| Production Reasoner API | vLLM + `vllm-cosmos3` from Framework | Plugin registers `Cosmos3ReasonerForConditionalGeneration` |
| Training, post-training, task eval | Not in this repo yet | Framework; README marks post-training recipes **[Coming Soon]** |

Clone path used by cookbooks:

```bash
mkdir -p packages
git clone https://github.com/NVIDIA/cosmos-framework.git packages/cosmos3
cd packages/cosmos3
export GIT_LFS_SKIP_SMUDGE=1
uv sync --all-extras --group=cu130-train   # or cu128-train on CUDA 12.x
```

## OpenMDW-1.1 license

NVIDIA Cosmos **source code and models** are released under the [OpenMDW License Agreement, version 1.1 (OpenMDW-1.1)](https://openmdw.ai/license/1-1/). The full text is in the repository root `LICENSE`. Cookbook notebooks declare `SPDX-License-Identifier: OpenMDW-1.1`.

### Scope: Model Materials

Under the agreement, **Model Materials** means:

1. One or more machine learning models (architecture and parameters), and  
2. All related artifacts (associated data, documentation, and software) provided under the agreement.

### Grants and distribution

| Topic | Terms |
| --- | --- |
| **Permission** | Free of charge, to deal in Model Materials without restriction, including copyright, patent, database, and trade secret rights—subject to compliance with the agreement |
| **Distribution** | If you distribute any portion of Model Materials, include (1) a copy of the agreement and (2) all applicable copyright and origin notices from the materials |
| **Outputs** | No restrictions or obligations on use, modification, or sharing of **outputs** generated by using the Model Materials |
| **Patent retaliation** | Rights terminate if you file, maintain, or voluntarily participate in a lawsuit asserting the Model Materials infringe patent or copyright—unless that suit responds to a corresponding suit first brought against you |

### Disclaimers and your responsibilities

The Model Materials are provided **“AS IS”** without warranty (merchantability, fitness, title, non-infringement, accuracy, latent defects) to the fullest extent permitted by law.

You are solely responsible for:

1. Clearing rights of other persons that may apply to the Model Materials or any use thereof (including copyrights or other rights embodied in the materials)  
2. Obtaining necessary consents, permissions, or other rights for any use  
3. Performing due diligence or other investigations into the Model Materials or anything incorporated therein  

Providers of the Model Materials are not liable for claims arising from the materials or their use.

### Custom licensing

For a license outside OpenMDW-1.1, contact **[cosmos-license@nvidia.com](mailto:cosmos-license@nvidia.com)**.

<Warning>
OpenMDW-1.1 governs NVIDIA Cosmos source and models in this repository. **Third-party packages** installed by setup commands (PyTorch, Diffusers, vLLM, Hugging Face Hub, guardrails, and others) remain under their own licenses—see [Third-party dependencies](#third-party-dependencies).
</Warning>

## Known model limitations

Cosmos 3 can produce artifacts in long, high-resolution, or physically complex outputs. Documented failure modes include:

| Category | Examples |
| --- | --- |
| **Temporal / motion** | Temporal inconsistency, unstable camera or object motion |
| **Multimodal alignment** | Inaccurate sound–video alignment, imperfect action–state consistency |
| **Geometry / physics** | Object morphing, inaccurate 3D structure, implausible physical dynamics |

<Warning>
Applications that require physically grounded simulation, **safety-critical control**, or complex multi-agent behavior need additional validation, guardrails, and system-level safety analysis before deployment—not reliance on raw model output alone.
</Warning>

### Safety guardrails (Generator)

Cosmos 3 Generator integrations ship **safety guardrails** (`cosmos_guardrail` in Diffusers installs) that screen prompts and blur faces in generated output. vLLM-Omni exposes per-request control via `extra_params.guardrails` (default on in several cookbooks; action robotics examples often disable guardrails for throughput). Server-wide disable uses a deploy config (`guardrails: false` in `model_config`); a dedicated `--cosmos3-no-guardrails` flag is noted as a future release item in the README.

Disabling guardrails does not remove the model limitations above; it only changes prompt/output screening behavior.

## Release cadence and version history

### Where to look

| Artifact | Location | Contents |
| --- | --- | --- |
| **Release cadence table** | `RELEASE.md` | Prior platform milestones with dates |
| **Cosmos 3 announcement** | `README.md` → News | May 31, 2026 release: Hugging Face collection, Framework workflows, technical report link |
| **Inference benchmarks** | `inference_benchmarks.md` | Generator latency and Reasoner serving metrics (updated incrementally) |

### Documented milestones (`RELEASE.md`)

| Version | Description | Date |
| --- | --- | --- |
| v1.0 | Initial diffusion and autoregressive WFMs release | 2025-01-06 |
| v0.1 | Initial tokenizer release | 2024-11-06 |

`RELEASE.md` references detailed notes at `release_notes/v0p1.md`; that path is not present in the current repository checkout—use `RELEASE.md` and README News for authoritative dates until release notes are published in-tree.

### Cosmos 3 (current generation)

:::updates
@update Cosmos 3 — May 31, 2026 — Models published in the [NVIDIA Cosmos 3 Hugging Face collection](https://huggingface.co/collections/nvidia/cosmos3). [Cosmos Framework](https://github.com/NVIDIA/cosmos-framework) provides runnable setup, inference, training, and evaluation workflows. Technical report: [Cosmos 3 Technical Report](https://research.nvidia.com/labs/cosmos-lab/cosmos3/technical-report.pdf).
:::

### In-repo capabilities still marked Coming Soon

| Capability | Status in README / cookbooks |
| --- | --- |
| Post-training recipes (vision, action, reasoner) + task-specific evaluation | Coming Soon (Framework) |
| Reasoner with Transformers | Coming soon |
| vLLM-Omni upstream (all modalities in stock `vllm-omni`) | Partial upstreaming via [vllm-omni#3454](https://github.com/vllm-project/vllm-omni/pull/3454); `vllm/vllm-omni:cosmos3` Docker image is the full-modality official build until merge |

## Third-party dependencies

> This project may download and install additional third-party open source software projects. Review the license terms of those projects before use.

Setup commands across README and `cookbooks/cosmos3/README.md` commonly install or reference:

| Dependency | Typical use | Install / source pointer |
| --- | --- | --- |
| **PyTorch / torchvision** | All GPU backends | `uv pip` with `--torch-backend=cu130` or `cu128` |
| **Diffusers** (git) | Generator research, `Cosmos3OmniPipeline` | `git+https://github.com/huggingface/diffusers.git` |
| **transformers**, **accelerate**, **huggingface_hub** | Model loading, HF auth | Pip alongside Diffusers or vLLM |
| **vLLM** | Reasoner production serving | `vllm==0.21.0` (cu130) or `vllm==0.19.1` (cu128) |
| **vllm-cosmos3** | Reasoner architecture plugin | `cosmos-framework.git#subdirectory=packages/vllm-cosmos3` |
| **vLLM-Omni** | Generator OpenAI-compatible API | `vllm/vllm-omni:cosmos3` Docker image or PR-branch pip install |
| **cosmos_guardrail** | Generator prompt/output safety | Diffusers venv install list |
| **av**, **imageio**, **imageio-ffmpeg** | Video I/O | Diffusers path |
| **NVIDIA NGC PyTorch containers** | Recommended base images | `nvcr.io/nvidia/pytorch:25.09-py3` (CUDA 13) or `25.06-py3` (CUDA 12) |

### Sample and asset dependencies

Action cookbooks include a **LeRobot-format DROID** sample under `cookbooks/cosmos3/generator/action/assets/droid_lerobot_example/`. Reasoner cookbooks may fetch vision assets from **`nvidia-cosmos/cosmos-dependencies`** (see reasoner README input URLs). Those assets are governed by their respective repositories and licenses, not only OpenMDW-1.1.

### Architectural third-party mentions

- Generator vLLM-Omni loads a checkpoint that includes a **Qwen3-VL-based** reasoner path alongside the diffusion path.  
- Reasoner serving follows **Qwen3-VL-compatible** chat message conventions for image and video inputs.  
- Hugging Face **gated** Cosmos3 model repos require authentication (`uvx hf auth login` or `HF_TOKEN`).

<Note>
The Cosmos Framework requires **`uv >= 0.11.3`** for `pyproject.toml` parsing and `--torch-backend` values such as `cu130`. Older `uv` versions fail sync/install with opaque errors—upgrade via `uv self update` before Framework work.
</Note>

## Related pages

<CardGroup>
  <Card title="Overview" href="/overview">
    Cosmos 3 Reasoner vs Generator surfaces, modalities, and the shortest first-run path.
  </Card>
  <Card title="Choose an integration" href="/choose-integration">
    Decision matrix for Diffusers, vLLM-Omni, vLLM, Framework, and coming-soon Transformers.
  </Card>
  <Card title="Cookbook environment setup" href="/cookbook-environment">
    Shared uv/Docker setup, HF auth, CUDA tags, and Framework clone/sync.
  </Card>
  <Card title="Inference benchmarks" href="/inference-benchmarks">
    Published Generator latency and Reasoner vLLM serving tables.
  </Card>
  <Card title="Troubleshooting" href="/troubleshooting">
    CUDA/driver pairing, NGC containers, uv version, and DeepGEMM workarounds.
  </Card>
</CardGroup>