---
# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0

title: "Llama Nemotron Models"
description: ""
---

This page provides detailed technical specifications for the Nemotron model family supported by NeMo Customizer. For information about supported features and capabilities, refer to [Tested Models](/documentation/customizer-reference/models/model-catalog).

## Llama 3.1 Nemotron Nano 8B v1

| Property | Value |
|----------|--------|
| Creator | NVIDIA |
| Architecture | transformer |
| Description | Llama 3.1 Nemotron Nano 8B v1 is a compact, instruction-tuned model for efficient customization and deployment. |
| Max I/O Tokens | 4096 |
| Parameters | 8 billion |
| Training Data | Not specified |
| Default Name | nvidia/Llama-3.1-Nemotron-Nano-8B-v1 |
| Hugging Face | [nvidia/Llama-3.1-Nemotron-Nano-8B-v1](https://huggingface.co/nvidia/Llama-3.1-Nemotron-Nano-8B-v1) |
| NIM | [nvidia/llama-3.1-nemotron-nano-8b-v1](https://catalog.ngc.nvidia.com/orgs/nim/teams/nvidia/containers/llama-3.1-nemotron-nano-8b-v1?version=1.8.4) |

### Training Options

- **LoRA**: 1x 80GB GPU, tensor parallel size 1, pipeline parallel size 1
- **Full SFT**: 4x 80GB GPU, tensor parallel size 2, pipeline parallel size 1

### Deployment Configuration

- **LoRA**:
 - NIM Image: `nvcr.io/nim/nvidia/llm-nim:1.15.5`
 - GPU Count: 1x 80GB
- **Full SFT**:
 - NIM Image: `nvcr.io/nim/nvidia/llm-nim:1.15.5`
 - GPU Count: 1x 80GB
 - Additional Environment Variables:
 - `NIM_MODEL_PROFILE`: `vllm`

## NVIDIA Nemotron Nano 9B v2

| Property | Value |
|----------|--------|
| Creator | NVIDIA |
| Architecture | transformer |
| Description | NVIDIA Nemotron Nano 9B v2 is a compact, instruction-tuned model optimized for efficient customization and deployment. |
| Max I/O Tokens | 4096 |
| Parameters | 9 billion |
| Default Name | nvidia/NVIDIA-Nemotron-Nano-9B-v2 |
| Hugging Face | [nvidia/NVIDIA-Nemotron-Nano-9B-v2](https://huggingface.co/nvidia/NVIDIA-Nemotron-Nano-9B-v2) |
| NIM | [NVIDIA-Nemotron-Nano-9B-v2](https://catalog.ngc.nvidia.com/orgs/nim/teams/nvidia/containers/nvidia-nemotron-nano-9b-v2?version=latest) |

### Training Options

- **LoRA**: 4x 80GB GPU, tensor parallel size 1, pipeline parallel size 1
- **Full SFT**: 4x 80GB GPU, tensor parallel size 2, pipeline parallel size 1

### Deployment Configuration

- **LoRA**:
 - NIM Image: `nvcr.io/nim/nvidia/llm-nim:1.15.5`
 - GPU Count: 1x 80GB
- **Full SFT**:
 - NIM Image: `nvcr.io/nim/nvidia/llm-nim:1.15.5`
 - GPU Count: 1x 80GB
 - Additional Environment Variables:
 - `NIM_MODEL_PROFILE`: `vllm`

## NVIDIA Nemotron 3 Nano 30B A3B

| Property | Value |
|----------|--------|
| Creator | NVIDIA |
| Architecture | Hybrid Mixture of Experts (MoE) - Mamba-2 + Transformer |
| Description | Nemotron-3-Nano-30B-A3B-BF16 is a large language model (LLM) trained from scratch by NVIDIA, and designed as a unified model for both reasoning and non-reasoning tasks. Uses configurable reasoning via chat template. |
| Max I/O Tokens | 2048 |
| Parameters | 30B total (3.5B active) |
| MoE Configuration | 128 experts + 1 shared expert, 6 experts activated per token |
| Supported Languages | English, German, Spanish, French, Italian, Japanese |
| Default Name | nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 |
| Hugging Face | [nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16](https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16) |
| NIM | [Nemotron-3-Nano-30B-A3B](https://catalog.ngc.nvidia.com/orgs/nim/teams/nvidia/containers/nemotron-3-nano?version=2.0.1) |

### Training Options

- **LoRA**: 2x 80GB GPU, tensor parallel size 1, expert parallel size 2, pipeline parallel size 1
- **Full SFT**: 8x 80GB GPU, tensor parallel size 1, expert parallel size 8, pipeline parallel size 1

<Note>

**MoE Parallelism Constraints**

MoE models only support expert parallelism for distributing experts across GPUs. When `expert_parallel_size > 1`, `tensor_parallel_size` must be set to 1. Additionally, `expert_parallel_size` must evenly divide the number of GPUs. These constraints apply to training parallelism only and NIM deployment may use different GPU counts optimized for inference.

</Note>
### Deployment Configuration

- **Full SFT**:
 - NIM Image: `nvcr.io/nim/nvidia/nemotron-3-nano:1.7.0-variant`
 - GPU Count: 2x 80GB

<Note>

Deployment for LoRA using NIM is not supported for this model.

</Note>
## NVIDIA Nemotron 3 Super 120B A12B

| Property | Value |
|----------|--------|
| Creator | NVIDIA |
| Architecture | Mixture of Experts (MoE) |
| Description | Nemotron-3-Super-120B-A12B-BF16 is a large MoE language model from NVIDIA designed for high-capacity reasoning and instruction-following tasks. |
| Max I/O Tokens | 4096 |
| Parameters | 120B total (12B active) |
| Default Name | nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16 |
| Hugging Face | [nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16](https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16) |

### Training Options

- **LoRA**: 8x 80GB GPU, tensor parallel size 1, expert parallel size 8, pipeline parallel size 1

<Note>

**MoE Parallelism Constraints**

MoE models only support expert parallelism for distributing experts across GPUs. When `expert_parallel_size > 1`, `tensor_parallel_size` must be set to 1. Additionally, `expert_parallel_size` must evenly divide the number of GPUs. These constraints apply to training parallelism only and NIM deployment may use different GPU counts optimized for inference.

</Note>
### Deployment Configuration

- **LoRA**:
 - NIM Image: `nvcr.io/nim/nvidia/nemotron-3-super-120b-a12b:1.8.1-variant`
 - GPU Count: 8x 80GB
 - Additional Environment Variables:
 - `NIM_WORKSPACE`: `/model-store`
 - `NIM_PIPELINE_PARALLEL_SIZE`: `8`
 - `NIM_MAX_MODEL_LEN`: `4096`
