Mistral Small 4 model is a powerful hybrid model with the capability of acting as both a general instruction model and a reasoning model.
Mistral Small 4 119B A6B Container Overview
Description:
This container houses Mistral Small 4 model which, is a powerful hybrid model with the capability of acting as both a general instruction model and a reasoning model. It unifies the capabilities of three different model families - Instruct, Reasoning ( previous called Magistral ), and Devstral - into a single, unified model.
With it's multimodal capabilities, efficient architecture and it's flexible mode switching, it's a powerful general model for any task. In a latency-optimized setup, Mistral Small 4 achieves 40% reduction End to End completion time, with a throughput-optimized setup, it achieves 3x more requests per second vs Mistral Small 3.
The container components are ready for commercial use.
License/Terms of Use:
GOVERNING TERMS: The NIM container is governed by the NVIDIA Software License Agreement and Product-Specific Terms for NVIDIA AI Products. Use of this model is governed by the NVIDIA Open Model License Agreement. Additional Information: Apache 2.0 License.
You are responsible for ensuring that your use of NVIDIA provided models complies with all applicable laws.
Deployment Geography:
Global
Release Date:
Build.NVIDIA.com: 03/16/2026 via link
Huggingface: 03/16/2026 via link
Mistral Small 4 119B A6B NIM:
The Mistral Small 4 119B A6B Container includes the Mistral Small 4 119B A6B model.
| Model Name & Link | Use Case | How to Pull the Model |
|---|---|---|
| Mistral Small 4 119B A6B https://build.nvidia.com/mistralai/mistral-small-4-119b-2603 | A powerful hybrid model with the capability of acting as both a general instruction model and a reasoning model. | Automatic |
Deployment Details:
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.
Container Version(s):
nvcr.io/nim/mistralai/mistral-small-4-119b-2603:1.7.0-variant
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. When downloaded or used in accordance with our terms of service, 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.
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.
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 VLM NIM page for release documentation, deployment guides and more.
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Get access to community knowledge base articles and support cases (https://forums.developer.nvidia.com/)