> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/nemo/automodel/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/nemo/automodel/_mcp/server.

# Model Coverage Overview

NeMo AutoModel integrates with Hugging Face `transformers`. Any LLM or VLM that can be instantiated through `transformers` can also be used using NeMo AutoModel, subject to runtime, third-party software dependencies, and feature compatibility.

## Supported Hugging Face Auto Classes

| Auto Class                           | Task                            | Status    | Details                                                                |
| ------------------------------------ | ------------------------------- | --------- | ---------------------------------------------------------------------- |
| `AutoModelForCausalLM`               | Text Generation (LLM)           | Supported | See [LLM model list](/model-coverage/large-language-models/overview).  |
| Block-Diffusion LLMs                 | Text Generation (Diffusion LLM) | Supported | See [Diffusion LLM model list](/model-coverage/dllm/overview).         |
| `AutoModelForImageTextToText`        | Image-Text-to-Text (VLM)        | Supported | See [VLM model list](/model-coverage/vision-language-models/overview). |
| Custom multimodal models             | Unified multimodal training     | Supported | See [Multimodal model list](/model-coverage/multimodal/overview).      |
| `AutoModelForSequenceClassification` | Sequence Classification         | WIP       | Early support; interfaces may change.                                  |
| Diffusers Pipelines                  | Diffusion Generation (T2I, T2V) | Supported | See [Diffusion model list](/model-coverage/diffusion/overview).        |
| `NeMoAutoModelBiEncoder`             | Embedding Models                | Supported | See [Embedding model list](/model-coverage/embedding-models/overview). |
| `NeMoAutoModelCrossEncoder`          | Reranking Models                | Supported | See [Reranking model list](/model-coverage/reranking-models/overview). |

## Release Log

The table below tracks when model support and key features were added across NeMo AutoModel releases. For the full list of tested architectures and example configs, see the [LLM](/model-coverage/large-language-models/overview), [VLM](/model-coverage/vision-language-models/overview), and [Multimodal](/model-coverage/multimodal/overview) pages.

| Release              | Date     | New Models                                                                                                                                                                                                                         | Key Features                                                                                                                                                 |
| -------------------- | -------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| **0.3.0** (upcoming) | —        | Kimi-VL, Kimi-K25-VL, Gemma 3n, Nemotron-Parse, Qwen3-VL-MoE, Qwen3-Omni, InternVL 3.5, Ministral3, Phi-4-multimodal, Devstral-Small-2, Step-3.5-Flash, Qwen3-Next, Nemotron-3-Nano-30B, FLUX.1-dev, Wan 2.1 T2V, HunyuanVideo 1.5 | MoE LoRA, expanded VLM coverage, diffusion model training (flow matching)                                                                                    |
| **0.2.0**            | Dec 2025 | GPT-OSS 20B/120B, Qwen3, Qwen3-MoE, GLM-4/4-MoE, Qwen2.5-VL, Qwen3-VL                                                                                                                                                              | Single- and multi-turn tool calling, streaming dataset, QAT for SFT, sequence classification, async DCP checkpointing, MLflow, CP + sequence packing for MoE |
| **0.1.0**            | Oct 2025 | DeepSeek V3/V3.2, 40+ LLM architectures, Gemma 3 VLM                                                                                                                                                                               | Pretraining, knowledge distillation, FP8 (torchao), pipeline parallelism, HSDP, auto pipelining, ColumnMapped dataset                                        |
| **0.1.0a0**          | Sep 2025 | Initial LLM and VLM support (Llama, Mistral, Qwen2, Gemma, Phi, and more)                                                                                                                                                          | MegatronFSDP, packed sequences, Triton LoRA kernels                                                                                                          |

## Day-0 Support

* NeMo AutoModel closely tracks the latest `transformers` version and updates its dependency regularly.
* New models released on the Hugging Face Hub may require the latest `transformers` version, necessitating a package upgrade.
* We are working on a CI pipeline that automatically bumps the supported `transformers` version when a new release is detected, enabling even faster day-0 support.

## Custom Model Registry

NeMo AutoModel includes a custom model registry that allows teams to:

* Add custom implementations to extend support to models not yet covered upstream.
* Provide optimized or faster implementations for specific models while retaining the same AutoModel interface.

## Having Issues?

If a model from the Hub doesn't work as expected, see the [Troubleshooting Unsupported Models](/model-coverage/overview) guide for common issues and solutions.