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.

AutoModelForImageTextToText

Image-Text-to-Text (VLM)

Supported

See VLM model list.

AutoModelForSequenceClassification

Sequence Classification

WIP

Early support; interfaces may change.

Diffusers Pipelines

Diffusion Generation (T2I, T2V)

Supported

See Diffusion model list.

NeMoAutoModelBiEncoder

Embedding Models

Supported

See Embedding model list.

NeMoAutoModelCrossEncoder

Reranking Models

Supported

See Reranking model list.

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 and VLM 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 Guide for common issues and solutions.