Instructions to use RedHatAI/NVIDIA-Nemotron-3-Super-120B-A12B-BF16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use RedHatAI/NVIDIA-Nemotron-3-Super-120B-A12B-BF16 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="RedHatAI/NVIDIA-Nemotron-3-Super-120B-A12B-BF16", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("RedHatAI/NVIDIA-Nemotron-3-Super-120B-A12B-BF16", trust_remote_code=True)
model = AutoModelForMultimodalLM.from_pretrained("RedHatAI/NVIDIA-Nemotron-3-Super-120B-A12B-BF16", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use RedHatAI/NVIDIA-Nemotron-3-Super-120B-A12B-BF16 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "RedHatAI/NVIDIA-Nemotron-3-Super-120B-A12B-BF16"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "RedHatAI/NVIDIA-Nemotron-3-Super-120B-A12B-BF16",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/RedHatAI/NVIDIA-Nemotron-3-Super-120B-A12B-BF16

SGLang

How to use RedHatAI/NVIDIA-Nemotron-3-Super-120B-A12B-BF16 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "RedHatAI/NVIDIA-Nemotron-3-Super-120B-A12B-BF16" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "RedHatAI/NVIDIA-Nemotron-3-Super-120B-A12B-BF16",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "RedHatAI/NVIDIA-Nemotron-3-Super-120B-A12B-BF16" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "RedHatAI/NVIDIA-Nemotron-3-Super-120B-A12B-BF16",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use RedHatAI/NVIDIA-Nemotron-3-Super-120B-A12B-BF16 with Docker Model Runner:
```
docker model run hf.co/RedHatAI/NVIDIA-Nemotron-3-Super-120B-A12B-BF16
```

robgreenberg3 commited on Mar 27

Commit

46e01d8

1 Parent(s): 94e59f9

Update README.md

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@@ -4,6 +4,19 @@ license: other
 license_name: nvidia-nemotron-open-model-license
 license_link: >-
   https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-nemotron-open-model-license/
 pipeline_tag: text-generation
 language:
 - en
@@ -25,7 +38,13 @@ datasets:
 track_downloads: true
 ---
-# NVIDIA-Nemotron-3-Super-120B-A12B-BF16
 <div align="center" style="line-height: 1;">
 <a href="https://build.nvidia.com/nvidia/nemotron-3-super-120b-a12b" target="_blank" style="margin: 2px;">

 license_name: nvidia-nemotron-open-model-license
 license_link: >-
   https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-nemotron-open-model-license/
+name: RedHatAI/NVIDIA-Nemotron-3-Super-120B-A12B-BF16
+description: Nemotron-3-Super-120B-A12B-BF16 is a large language model (LLM) trained by NVIDIA, designed to deliver strong agentic, reasoning, and conversational capabilities.
+readme: https://huggingface.co/RedHatAI/NVIDIA-Nemotron-3-Super-120B-A12B-BF16/main/README.md
+tasks:
+- text-to-text
+- text-generation
+- image-to-text
+- reasoning
+- tool-calling
+provider: NVIDIA
+validated_on:
+  - RHOAI 3.4
+  - RHAIIS 3.4
 pipeline_tag: text-generation
 language:
 - en
 track_downloads: true
 ---
+<h1 align: center; style="display: flex; align-items: center; gap: 10px; margin: 0;">
+  NVIDIA-Nemotron-3-Super-120B-A12B-BF16
+  <img src="https://www.redhat.com/rhdc/managed-files/Catalog-Validated_model_0.png" alt="Model Icon" width="40" style="margin: 0; padding: 0;" />
+</h1>
+<a href="https://www.redhat.com/en/products/ai/validated-models" target="_blank" style="margin: 0; padding: 0;">
+<img src="https://www.redhat.com/rhdc/managed-files/Validated_badge-Dark.png" alt="Validated Badge" width="250" style="margin: 0; padding: 0;" />
+</a>
 <div align="center" style="line-height: 1;">
 <a href="https://build.nvidia.com/nvidia/nemotron-3-super-120b-a12b" target="_blank" style="margin: 2px;">