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README.md

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+---
+license: other
+license_name: nvidia-open-model-license
+license_link: >-
+  https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license
+library_name: cosmos
+tags:
+- nvidia
+- cosmos
+- diffusers
+pipeline_tag: image-to-video
+extra_gated_prompt: >-
+  # NVIDIA Open Model License Agreement
+
+  Version Release Date: June 16, 2025
+
+  This NVIDIA Open Model License Agreement (the "<ins>Agreement</ins>") is a
+  legal agreement between the Legal Entity You represent, or if no entity is
+  identified, You and NVIDIA Corporation and its Affiliates
+  ("<ins>NVIDIA</ins>") and governs Your use of the Models that NVIDIA provides
+  to You under this Agreement. NVIDIA and You are each a "<ins>party</ins>" and
+  collectively the "<ins>parties</ins>."
+
+  NVIDIA models released under this Agreement are intended to be used
+  permissively and enable the further development of AI technologies. Subject to
+  the terms of this Agreement, NVIDIA confirms that:
+
+  * Models are commercially usable.
+
+  * You are free to create and distribute Derivative Models.
+
+  * NVIDIA does not claim ownership to any outputs generated using the Models or
+  Model Derivatives.
+
+  By using, reproducing, modifying, distributing, performing or displaying any
+  portion or element of the Model or Derivative Model, or otherwise accepting
+  the terms of this Agreement, you agree to be bound by this Agreement.
+
+  ## 1. Definitions
+
+  The following definitions apply to this Agreement:
+
+    1.1. "<ins>NVIDIA Cosmos Model</ins>" means a multimodal Model shared under this Agreement.
+
+    1.2. "<ins>Derivative Model</ins>" means all (a) modifications to the Model, (b) works based on the Model, and (c) any other derivative works of the Model. An output is not a Derivative Model.
+
+    1.3. "<ins>Legal Entity</ins>" means the union of the acting entity and all other entities that <ins>control</ins>, are controlled by, or are under common control with that entity. For the purposes of this definition, "<ins>control</ins>" means (a) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (b) ownership of fifty percent (50%) or more of the outstanding shares, or (c) beneficial ownership of such entity.
+
+    1.4. "<ins>Model</ins>" means the machine learning model, software, checkpoints, learnt weights, algorithms, parameters, configuration files and documentation shared under this Agreement.
+
+    1.5. "<ins>You</ins>" or "<ins>Your</ins>" means an individual or Legal Entity exercising permissions granted by this Agreement.
+
+  ## 2. Conditions for Use, License Grant, AI Ethics and IP Ownership
+
+    2.1. Conditions for Use. The Model and any Derivative Model are subject to additional terms as described in Section 2 and Section 3 of this Agreement and govern Your use. If You institute copyright or patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Model or a Derivative Model constitutes direct or contributory copyright or patent infringement, then any licenses granted to You under this Agreement for that Model or Derivative Model will terminate as of the date such litigation is filed. If You bypass, disable, reduce the efficacy of, or circumvent any technical limitation, safety guardrail or associated safety guardrail hyperparameter, encryption, security, digital rights management, or authentication mechanism contained in the Model, your rights under this Agreement will automatically terminate. NVIDIA may update this Agreement to comply with legal and regulatory requirements at any time and You agree to either comply with any updated license or cease Your copying, use, and distribution of the Model and any Derivative Model.
+
+    2.2. License Grant. The rights granted herein are explicitly conditioned on Your full compliance with the terms of this Agreement. Subject to the terms and conditions of this Agreement, NVIDIA hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, revocable (as stated in Section 2.1) license to publicly perform, publicly display, reproduce, use, create derivative works of, make, have made, sell, offer for sale, distribute (through multiple tiers of distribution) and import the Model.
+
+    2.3. AI Ethics. Use of the Models under the Agreement must be consistent with NVIDIA's Trustworthy AI terms found at https://www.nvidia.com/en-us/agreements/trustworthy-ai/terms/.
+
+    2.4. NVIDIA owns the Model and any Model Derivatives created by NVIDIA. Subject to NVIDIA's underlying ownership rights in the Model or its Model Derivatives, You are and will be the owner of Your Model Derivatives. NVIDIA claims no ownership rights in outputs. You are responsible for outputs and their subsequent uses. Except as expressly granted in this Agreement, (a) NVIDIA reserves all rights, interests and remedies in connection with the Model and (b) no other license or right is granted to you by implication, estoppel or otherwise.
+
+  ## 3. Redistribution
+
+  You may reproduce and distribute copies of the Model or Derivative Models
+  thereof in any medium, with or without modifications, provided that You meet
+  the following conditions:
+
+    3.1. If you distribute the Model, You must give any other recipients of the Model a copy of this Agreement and include the following attribution notice within a "Notice" text file with such copies: "Licensed by NVIDIA Corporation under the NVIDIA Open Model License";
+
+    3.2. If you distribute or make available a NVIDIA Cosmos Model, or a product or service (including an AI model) that contains or uses a NVIDIA Cosmos Model, use a NVIDIA Cosmos Model to create a Derivative Model, or use a NVIDIA Cosmos Model or its outputs to create, train, fine tune, or otherwise improve an AI model, you will include "Built on NVIDIA Cosmos" on a related website, user interface, blogpost, about page, or product documentation; and
+
+    3.3. You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Models as a whole, provided Your use, reproduction, and distribution of the Model otherwise complies with the conditions stated in this Agreement.
+
+  ## 4. Trademarks
+
+  This Agreement does not grant permission to use the trade names, trademarks,
+  service marks, or product names of NVIDIA, except as required for reasonable
+  and customary use in describing the origin of the Model and reproducing the
+  content of the "Notice" text file.
+
+  ## **5. Disclaimer of Warranty**
+
+  **Unless required by applicable law or agreed to in writing, NVIDIA provides
+  the Model on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,
+  either express or implied, including, without limitation, any warranties or
+  conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
+  PARTICULAR PURPOSE. You are solely responsible for determining the
+  appropriateness of using or redistributing the Model, Derivative Models and
+  outputs and assume any risks associated with Your exercise of permissions
+  under this Agreement.**
+
+  ## **6. Limitation of Liability**
+
+  **In no event and under no legal theory, whether in tort (including
+  negligence), contract, or otherwise, unless required by applicable law (such
+  as deliberate and grossly negligent acts) or agreed to in writing, will NVIDIA
+  be liable to You for damages, including any direct, indirect, special,
+  incidental, or consequential damages of any character arising as a result of
+  this Agreement or out of the use or inability to use the Model, Derivative
+  Models or outputs (including but not limited to damages for loss of goodwill,
+  work stoppage, computer failure or malfunction, or any and all other
+  commercial damages or losses), even if NVIDIA has been advised of the
+  possibility of such damages.**
+
+  ## 7. Indemnity
+
+  You will indemnify and hold harmless NVIDIA from and against any claim by any
+  third party arising out of or related to your use or distribution of the
+  Model, Model Derivatives or outputs.
+
+  ## 8. Feedback
+
+  NVIDIA appreciates your feedback, and You agree that NVIDIA may use it without
+  restriction or compensation to You.
+
+  ## 9. Governing Law
+
+  This Agreement will be governed in all respects by the laws of the United
+  States and the laws of the State of Delaware, without regard to conflict of
+  laws principles or the United Nations Convention on Contracts for the
+  International Sale of Goods. The state and federal courts residing in Santa
+  Clara County, California will have exclusive jurisdiction over any dispute or
+  claim arising out of or related to this Agreement, and the parties irrevocably
+  consent to personal jurisdiction and venue in those courts; except that,
+  either party may apply for injunctive remedies or an equivalent type of urgent
+  legal relief in any jurisdiction.
+
+  ## 10. Trade and Compliance
+
+  You agree to comply with all applicable export, import, trade and economic
+  sanctions laws and regulations, as amended, including without limitation U.S.
+  Export Administration Regulations and Office of Foreign Assets Control
+  regulations. These laws include restrictions on destinations, end-users and
+  end-use.
+extra_gated_fields:
+  By clicking Submit below, I accept the terms of the NVIDIA Open Model License Agreement and acknowledge that I am an adult of legal age of majority in the country in which the Cosmos Models will be used and have authority to accept this Agreement: checkbox
+extra_gated_description: >-
+  The information you provide will be collected, stored, processed and shared in
+  accordance with the [NVIDIA Privacy
+  Policy](https://www.nvidia.com/en-us/about-nvidia/privacy-policy/).
+extra_gated_button_content: Submit
+---
+
+# **Cosmos-Predict2.5: A Suite of Diffusion-based World Foundation Models**
+
+[**Cosmos**](https://huggingface.co/collections/nvidia/cosmos-predict2-68028efc052239369a0f2959) | [**Code**](https://github.com/nvidia-cosmos/cosmos-predict2) | [**Website**](https://research.nvidia.com/labs/dir/cosmos-predict2/)
+
+# Model Overview
+
+## Description
+
+**Cosmos-Predict2.5**: A family of highly performant pre-trained world foundation models purpose-built for generating physics-aware images, videos and world states for physical AI development.
+
+Cosmos-Predict2.5 diffusion models are a collection of diffusion based world foundation models that generate dynamic, high quality images and videos from text, image, or video inputs. It can serve as the building block for various applications or research that are related to world generation. The models are ready for commercial use under NVIDIA Open Model license agreement.
+
+**Model Developer**: NVIDIA
+
+## Model Versions
+
+The Cosmos-Predict2.5 diffusion-based model family includes the following models:
+
+- Cosmos-Predict2.5-2B
+  - Given a text, an image as the first frame, or a video predict the future frames.
+  - Produces 720P video with 16FPS
+- Cosmos-Predict2.5-14B
+  - Given a text, an image as the first frame, or a video predict the future frames.
+  - Produces 720P video with 16FPS
+
+### License
+
+This model is released under the  [NVIDIA Software & Model Evaluation License](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-and-model-evaluation-license/). For a custom license, please contact [[email protected]](mailto:[email protected]).
+
+### Deployment Geography:
+
+Global
+
+### Use Case:
+
+Physical AI: encompassing robotics, autonomous vehicles (AV), and more.
+
+### Release Date:
+
+TBD
+
+## Model Architecture
+
+Cosmos-Predict2.5-2B is a diffusion transformer model designed for video denoising in the latent space. The network is composed of interleaved self-attention, cross-attention and feedforward layers as its building blocks. The cross-attention layers allow the model to condition on input text throughout the denoising process. Before each layer, adaptive layer normalization is applied to embed the time information for denoising. When image or video is provided as input, their latent frames are concatenated with the generated frames along the temporal dimension. Augment noise is added to conditional latent frames to bridge the training and inference gap.
+
+## Input/Output Specifications
+
+* **Input**
+
+  * **Input Type(s)**: Text, Text+Image, Text+Video
+  * **Input Format(s)**:
+    * Text: String
+    * Image: jpg, png, jpeg, webp
+    * Video: mp4
+  * **Input Parameters**:
+    * Text: One-dimensional (1D)
+    * Image: Two-dimensional (2D)
+    * Video: Three-dimensional (3D)
+  * **Other Properties Related to Input**:
+    * The input string should contain fewer than 300 words and should provide descriptive content for world generation, such as a scene description, key objects or characters, background, and any specific actions or motions to be depicted within the 5-second duration.
+    * For the 720P model, the input image should be 1280×704; for the 480P model, use 832×480.
+    * The input video should consist of 5 frames, each with a resolution of 1280×704 for the 720P model, or 832×480 for the 480P model.
+* **Output**
+
+  * **Output Type(s)**: Video
+  * **Output Format(s)**: mp4
+  * **Output Parameters**: Three-dimensional (3D)
+  * **Other Properties Related to Output**: The generated video is a 5-second clip, with resolution and frame rate determined by the model variant used. For example, the 720P 16FPS model produces a video with a resolution of 1280×704 and a frame rate of 16 FPS.
+
+The video content visualizes the input text description as a short animated scene, capturing key elements within the specified time constraints.
+
+Our AI models are designed and/or optimized to run on NVIDIA GPU-accelerated systems. By leveraging NVIDIA's hardware (e.g. GPU cores) and software frameworks (e.g., CUDA libraries), the model achieves faster training and inference times compared to CPU-only solutions.
+
+## Software Integration
+
+**Runtime Engine(s):**
+
+* [Cosmos-Predict2](https://github.com/nvidia-cosmos/cosmos-predict2)
+* [Diffusers](https://github.com/huggingface/diffusers)
+
+```python
+import torch
+from diffusers import Cosmos2VideoToWorldPipeline
+from diffusers.utils import export_to_video, load_image
+
+# Available checkpoints: nvidia/Cosmos-Predict2-2B-Video2World, nvidia/Cosmos-Predict2-14B-Video2World
+model_id = "nvidia/Cosmos-Predict2-2B-Video2World"
+pipe = Cosmos2VideoToWorldPipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16)
+pipe.to("cuda")
+
+prompt = "A close-up shot captures a vibrant yellow scrubber vigorously working on a grimy plate, its bristles moving in circular motions to lift stubborn grease and food residue. The dish, once covered in remnants of a hearty meal, gradually reveals its original glossy surface. Suds form and bubble around the scrubber, creating a satisfying visual of cleanliness in progress. The sound of scrubbing fills the air, accompanied by the gentle clinking of the dish against the sink. As the scrubber continues its task, the dish transforms, gleaming under the bright kitchen lights, symbolizing the triumph of cleanliness over mess."
+negative_prompt = "The video captures a series of frames showing ugly scenes, static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, artifacting, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, visual noise, and flickering. Overall, the video is of poor quality."
+image = load_image(
+    "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/yellow-scrubber.png"
+)
+
+video = pipe(
+    image=image, prompt=prompt, negative_prompt=negative_prompt, generator=torch.Generator().manual_seed(1)
+).frames[0]
+export_to_video(video, "output.mp4", fps=16)
+```
+
+**Supported Hardware Microarchitecture Compatibility:**
+
+* NVIDIA Ampere
+* NVIDIA Blackwell
+* NVIDIA Hopper
+
+**Note**: Only BF16 precision is tested. Other precisions like FP16 or FP32 are not officially supported.
+
+## Inference
+
+**Acceleration Engine**: [PyTorch](https://pytorch.org/), [Transformer Engine](https://github.com/NVIDIA/TransformerEngine)
+
+**Operating System(s):**
+
+* Linux (We have not tested on other operating systems.)
+
+**System Requirements and Performance**
+
+Video2World (720p, 16FPS): This model requires 32.54 GB of GPU VRAM. The following table shows inference time for a single generation across different NVIDIA GPU hardware:
+
+| GPU Hardware           | Inference Runtime |
+| ---------------------- | ----------------- |
+| H100 SXM               | 228.8  s          |
+| H200 SXM               | 221.7  s          |
+| B200                   | 123.9  s          |
+| H100 NVL               | 355.7  s          |
+| H100 PCIe              | 378.5  s          |
+| H200 NVL               | 267.2  s          |
+| L40S                   | 2567.1 s          |
+| RTX PRO 6000 Blackwell | 452.2  s          |
+
+Text2Image: This model requires 26.02 GB of GPU VRAM.
+The following table shows inference time for a single generation across different NVIDIA GPU hardware:
+
+| GPU Hardware                            | Inference Runtime |
+| --------------------------------------- | ----------------- |
+| NVIDIA GB200                            | 3.39 sec          |
+| NVIDIA B200                             | 3.24 sec          |
+| NVIDIA RTX PRO 6000 Workstation Edition | 5.59 sec          |
+| NVIDIA H200 SXM                         | 9.02 sec          |
+| NVIDIA H200 NVL                         | 6.34 sec          |
+| NVIDIA H100 PCIe                        | 11.12 sec         |
+| NVIDIA H100 NVL                         | 5.05 sec          |
+| NVIDIA H20                              | 11.47 sec         |
+| NVIDIA L40S                             | 8.9 sec           |
+| NVIDIA RTX 6000 Ada Generation          | 11.94 sec         |
+
+# Usage
+
+* See [Cosmos-Predict2](https://github.com/nvidia-cosmos/cosmos-predict2) for details.
+
+# Evaluation
+
+Evaluation details for this model are forthcoming. Please visit our [website](https://research.nvidia.com/labs/dir/cosmos-predict2/) for updates and detailed benchmarks once available.
+
+**Data Collection Method**:
+
+* Automated
+
+**Labeling Method**:
+
+* Hybrid:  Human,Automated
+
+## Limitations
+
+Despite various improvements in world generation for Physical AI, Cosmos-Predict2 video2world models still face technical and application limitations for world prediction. In particular, they struggle to generate long, high-resolution videos without artifacts. Common issues include temporal inconsistency, camera and object motion instability, and imprecise interactions. The models may inaccurately represent 3D space, 4D space-time, or physical laws in the generated videos, leading to artifacts such as disappearing or morphing objects, unrealistic interactions, and implausible motions. As a result, applying these models for applications that require simulating physical law-grounded environments or complex multi-agent dynamics remains challenging.
+
+## Ethical Considerations
+
+NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications.  When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.
+
+Users are responsible for model inputs and outputs. Users are responsible for ensuring safe integration of this model, including implementing guardrails as well as other safety mechanisms, prior to deployment.
+
+For more detailed information on ethical considerations for this model, please see the subcards of Explainability, Bias, Safety & Security, and Privacy below. Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).
+
+### Plus Plus (++) Promise
+
+We value you, the datasets, the diversity they represent, and what we have been entrusted with. This model and its associated data have been:
+
+* Verified to comply with current applicable disclosure laws, regulations, and industry standards.
+* Verified to comply with applicable privacy labeling requirements.
+* Annotated to describe the collector/source (NVIDIA or a third-party).
+* Characterized for technical limitations.
+* Reviewed to ensure proper disclosure is accessible to, maintained for, and in compliance with NVIDIA data subjects and their requests.
+* Reviewed before release.
+* Tagged for known restrictions and potential safety implications.

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