# Model Catalog

Explore the model families and sizes supported by {{ncm_long_name}}.

!!! note
    For information on setting up model entities for customization, see the [Manage Model Entities](../manage-model-entities/index.md) guide.
    For fine-tuning and deployment tutorials, see the [Tutorials](../tutorials/index.md) guide.

## Before You Start

If downloading models hosted on Hugging Face, create a secret with your HuggingFace API key, then create a FileSet and Model Entity referencing the model. See [index](../manage-model-entities/index.md) for setup instructions.

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## Model Families

-   **[Llama Models](llama.md)**

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    View the available Llama models from Meta, ranging from 8 billion to 70 billion parameters.

-   **[Llama Nemotron Models](llama-nemotron.md)**

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    View the available Llama Nemotron models from NVIDIA, including Nano and Super variants for efficient and advanced instruction tuning.

-   **[Phi Models](phi.md)**

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    View the available Phi models from Microsoft, designed for strong reasoning capabilities with efficient deployment.

-   **[Embedding Models](embedding.md)**

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    View the available embedding models optimized for retrieval and question-answering tasks.

-   **[GPT-OSS Models](gpt-oss.md)**

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    View the available GPT-OSS models supported for customization.

-   **[Qwen Models](qwen.md)**

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    View the available Qwen models from Alibaba Cloud, including compact variants for efficient customization.

-   **[Mistral Models](mistral.md)**

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    View the available Mistral models, including Mistral and Ministral variants for instruction-following and reasoning tasks.


## Tested Models

The following table lists models that NVIDIA tested and their available features. While {{ncm_short_name}} works with all LLM NIM microservices, the table lists the models that NVIDIA tested. Models available for fine-tuning with {{ncm_short_name}} are not limited to those listed.

For detailed technical specifications of each model such as architecture, parameters, and token limits, refer to the [model family](#model-families) pages.

### Large Language Models

The following models support both chat and completion model training.

| Model | Train a Chat Model with Tool Calling | Fine-tuning Options | Sequence Packing[^1] | Inference with NIM | Reasoning |
|--|--|--|--|--|--|
| [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) | Yes | Full SFT, LoRA | Yes | Supported | No |
| [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct) | Yes | Full SFT, LoRA | Yes | Supported | No |
| [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) | Yes | Full SFT, LoRA | Yes | Supported | No |
| [nvidia/Llama-3.1-Nemotron-Nano-8B-v1](https://huggingface.co/nvidia/Llama-3.1-Nemotron-Nano-8B-v1) | No | Full SFT, LoRA | Yes | Supported | Yes |
| [nvidia/NVIDIA-Nemotron-Nano-9B-v2](https://huggingface.co/nvidia/NVIDIA-Nemotron-Nano-9B-v2) | No | Full SFT, LoRA | No | Supported | Yes |
| [nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16](https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16) | No | Full SFT, LoRA | No | Supported (only Full SFT) | Yes |
| [nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16](https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16) | No | LoRA | No | Supported | Yes |
| [microsoft/phi-4](https://huggingface.co/microsoft/phi-4) | No | Full SFT, LoRA | No | Supported | No |
| [openai/gpt-oss-20b](https://huggingface.co/openai/gpt-oss-20b) | Yes | Full SFT, LoRA | No | Supported | Yes |
| [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) | No | Full SFT, LoRA | No| Supported | Yes |
| [Qwen/Qwen3-0.6B](https://huggingface.co/Qwen/Qwen3-0.6B) | No | Full SFT, LoRA | No | Supported | Yes |
| [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) | No | Full SFT, LoRA | No | Supported | No |
| [mistralai/Ministral-3-3B-Instruct-2512](https://huggingface.co/mistralai/Ministral-3-3B-Instruct-2512) | No | Full SFT, LoRA | No | No | No |
| [mistralai/Ministral-3-3B-Reasoning-2512](https://huggingface.co/mistralai/Ministral-3-3B-Reasoning-2512) | No | Full SFT, LoRA | Yes | No | Yes |

[^1]: Read more on [sequence packing with NeMo Framework](https://docs.nvidia.com/nemo-framework/user-guide/latest/sft_peft/packed_sequence.html#)

### Embedding Models

| Model | Fine-tuning Options | Inference with NIM |
|--|--|--|
| [nvidia/llama-nemotron-embed-1b-v2](https://huggingface.co/nvidia/llama-nemotron-embed-1b-v2) | Full SFT, LoRA (merged) | Supported |

For detailed technical specifications and configuration information for embedding models, see the [Embedding Models](embedding.md) page.
