ContainersNVIDIADeepSeek-R1NVIDIALlama-3.1-Nemotron-70B-InstructNVIDIAPyTorch
CollectionsNVIDIAOmniverse Kit (FB)NVIDIADeepStream SDKNVIDIAOmniverse Kit App Streaming
ModelsNVIDIAStyleGAN3 pretrained modelsNVIDIAPeopleNetNVIDIATrafficCamNet
ResourcesNVIDIARiva Skills Quick Start
Helm ChartsNVIDIAGPU OperatorNVIDIANVIDIA NIM Operator
Mistral AI
Mistral AI
Nemotoron-Mini-4B-Instruct-ONNX-INT4-RTX
Model
Mistral AI
Mistral AI
Nemotoron-Mini-4B-Instruct-ONNX-INT4-RTX

Nemotron-Mini-4B Instruct model is for generating responses for roleplaying, retrieval augmented generation, and function calling. It is a small language model optimized through distillation, pruning and quantization for speed and on-device deployment.

Runs on RTX
This model is backed by NVIDIA's Plus Plus (++) Promise
to learn more about the quality of the datasets used to train this model.
FieldResponse
Intended Application & Domain:Game NPC Development
Model Type:Generative Pre-Trained Transformer (GPT)
Intended User:Enterprise developers building game NPCs.
Output:Text String(s)
Describe how the model works:Generates a response using the input text and context such as NPC background information.
Name the adversely impacted groups this has been tested to deliver comparable outcomes regardless of:Not Applicable
Verified to have met prescribed NVIDIA quality standards:Yes
Performance Metrics:Accuracy, Latency, and Throughput
Potential Known Risks:The model was trained on data that contains toxic language and societal biases originally crawled from the internet. Therefore, the model may amplify those biases and return toxic responses especially when prompted with toxic prompts. The model may generate answers that may be inaccurate, omit key information, or include irrelevant or redundant text producing socially unacceptable or undesirable text, even if the prompt itself does not include anything explicitly offensive. This issue could be exacerbated without the use of the recommended prompt template. The model may also amplify biases and return toxic responses especially when prompted with toxic prompts. If you are going to use this model in an agentic workflow, validate that the imported packages are from a trusted source to ensure end-to-end security.
Technical Limitation :The model was trained on data that contains toxic language and societal biases originally crawled from the internet. Therefore, the model may amplify those biases and return toxic responses especially when prompted with toxic prompts. The model may generate answers that may be inaccurate, omit key information, or include irrelevant or redundant text producing socially unacceptable or undesirable text, even if the prompt itself does not include anything explicitly offensive.
Licensing:NVIDIA Open Model License Agreement