A deployable inference container for serving a 30B dense multimodal causal language model with a perception encoder through industry-standard APIs.
Muse Glimmer Overview
Description:
A deployable inference container for serving Muse Glimmer, a 30B dense multimodal causal language model with a dedicated perception encoder, through industry-standard APIs. It supports local, always-on agentic workflows on NVIDIA GPU-accelerated systems, accepting interleaved text and image inputs to produce text output without requiring cloud infrastructure or network access.
The container components are ready for commercial or non-commercial use.
This container image is classified as a Pre-Release candidate (NVIDIA Software License Agreement).
Third-Party Community Consideration
The model embedded in the container is not owned or developed by NVIDIA. This model has been developed and built to a third-party's requirements for this application and use case; see link to Non-NVIDIA Muse Glimmer Model Card.
License/Terms of Use:
GOVERNING DOWNLOAD TERMS: Use of this container is governed by the NVIDIA Software License Agreement and Product-Specific Terms for NVIDIA AI Products.
You are responsible for ensuring that your use of NVIDIA provided models complies with all applicable laws.
Deployment Geography:
Global
Release Date:
NGC: 08/10/2026
Program Classes:
The NIM container includes the following model:
| Model Name & Link | Use Case | How to Pull the Model |
|---|---|---|
| Muse Glimmer | Local agentic workflows with multimodal input and text output | Automatic (embedded in container) |
Deployment Details:
The NIM container exposes industry-standard inference APIs for integration into applications and workflows.
API Endpoints:
/v1/chat/completions— Chat completions/v1/models— List available models/health/ready— Health check
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.
References:
Container Version(s)
dev1.fix6
Security Common Vulnerabilities and Exposures (CVEs)
Please review the Security Scanning tab on NGC to view the latest security scan results.
For certain open-source vulnerabilities listed in the scan results, NVIDIA provides a response in the form of a Vulnerability Exploitability eXchange (VEX) document. The VEX information can be reviewed and downloaded from the Security Scanning tab.
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. Developers should work with their internal developer team to ensure these software components meet requirements for the relevant industry and use case and address unforeseen product misuse.
Please report quality, risk, security vulnerabilities or NVIDIA AI Concerns here.
Get Help
Getting started with the NIM
Deploying and integrating the NIM is straightforward thanks to our industry standard APIs. Visit the NIM documentation for release documentation, deployment guides and more.
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