Instructions to use nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8 with Transformers:

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

pipe = pipeline("text-generation", model="nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8", 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("nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8", trust_remote_code=True)
model = AutoModelForMultimodalLM.from_pretrained("nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8", 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 nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8

SGLang

How to use nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8 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 "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8" \
    --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": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8",
		"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 "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8" \
        --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": "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8 with Docker Model Runner:
```
docker model run hf.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8
```

NVIDIA-Nemotron-3-Nano-30B-A3B-FP8 / nemo-evaluator-launcher-configs /local_nvidia_nemotron_3_nano_30b_a3b.yaml

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	# SPDX-FileCopyrightText: Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved.
	# SPDX-License-Identifier: Apache-2.0
	#
	# Licensed under the Apache License, Version 2.0 (the "License");
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS,
	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	# See the License for the specific language governing permissions and
	# limitations under the License.

	defaults:
	- execution: local
	- deployment: none
	- _self_

	execution:
	output_dir: ./results_nvidia_nemotron_3_nano_30b_a3b
	mounts:
	evaluation:
	./hf_cache: /root/.cache/huggingface
	env_vars:
	evaluation: {}

	target:
	api_endpoint:
	model_id: nvidia/nemotron-nano-3-30b-a3b
	url: https://integrate.api.nvidia.com/v1/chat/completions
	api_key_name: NGC_API_KEY # API Key with access to build.nvidia.com

	evaluation:
	env_vars:
	HF_TOKEN: HF_TOKEN
	JUDGE_API_KEY: JUDGE_API_KEY # API Key with access to gpt-4o for HLE
	HF_HOME: HF_HOME
	nemo_evaluator_config:
	config:
	params:
	max_new_tokens: 131072
	temperature: 0.99999
	top_p: 0.99999
	parallelism: 512
	request_timeout: 3600
	max_retries: 10
	extra:
	tokenizer: NVIDIA-Nemotron-Nano-3-30B-A3B-BF16
	tokenizer_backend: huggingface
	target:
	api_endpoint:
	adapter_config:
	use_caching: true
	tracking_requests_stats: true
	log_failed_requests: true
	use_request_logging: true
	max_logged_requests: 10
	use_response_logging: true
	max_logged_responses: 10
	tasks:
	- name: ns_bfcl_v3
	env_vars:
	HF_TOKEN: HF_TOKEN
	nemo_evaluator_config:
	config:
	params:
	temperature: 0.6
	top_p: 0.95
	parallelism: 32
	extra:
	num_repeats: 1
	args: ++use_client_parsing=False
	target:
	api_endpoint:
	adapter_config:
	use_caching: false
	- name: ns_bfcl_v4
	env_vars:
	HF_TOKEN: HF_TOKEN
	nemo_evaluator_config:
	config:
	params:
	max_new_tokens: 8192
	parallelism: 128
	temperature: 0.6
	top_p: 0.95
	extra:
	num_repeats: 1
	args: ++use_client_parsing=False
	- name: ns_livecodebench
	env_vars:
	HF_TOKEN: HF_TOKEN
	nemo_evaluator_config:
	config:
	params:
	extra:
	num_repeats: 8
	dataset_split: test_v5_2407_2412
	- name: ns_mmlu_pro
	env_vars:
	HF_TOKEN: HF_TOKEN
	nemo_evaluator_config:
	config:
	params:
	extra:
	num_repeats: 1
	args: "++prompt_config=eval/aai/mcq-10choices-boxed"
	- name: ns_gpqa
	env_vars:
	HF_TOKEN: HF_TOKEN
	nemo_evaluator_config:
	config:
	params:
	extra:
	num_repeats: 8
	args: "++prompt_config=eval/aai/mcq-4choices"
	- name: ns_aime2025
	env_vars:
	HF_TOKEN: HF_TOKEN
	JUDGE_API_KEY: JUDGE_API_KEY
	nemo_evaluator_config:
	config:
	params:
	extra:
	num_repeats: 64
	args: ++prompt_config=/prompt_templates/math-oai.yaml
	- name: ns_scicode
	env_vars:
	HF_TOKEN: HF_TOKEN
	JUDGE_API_KEY: JUDGE_API_KEY
	nemo_evaluator_config:
	config:
	params:
	extra:
	num_repeats: 8
	- name: ns_ifbench
	env_vars:
	HF_TOKEN: HF_TOKEN
	nemo_evaluator_config:
	config:
	params:
	extra:
	num_repeats: 8
	- name: ns_hle
	env_vars:
	HF_TOKEN: HF_TOKEN
	JUDGE_API_KEY: JUDGE_API_KEY
	nemo_evaluator_config:
	config:
	params:
	extra:
	num_repeats: 1
	judge_support: true
	judge:
	parallelism: 16
	model_id: openai/gpt-4o
	url: <OPENAI_API_URL_FOR_JUDGE>
	api_key: JUDGE_API_KEY