# 🚀 NeMo AutoModel
[](https://codecov.io/github/NVIDIA-NeMo/Automodel)
[](https://github.com/NVIDIA-NeMo/Automodel/actions/workflows/cicd-main.yml)
[](https://www.python.org/downloads/release/python-3110/)
[](CONTRIBUTING.md)
[](https://github.com/NVIDIA-NeMo/Automodel/stargazers/)
[📖 Documentation](https://docs.nvidia.com/nemo/automodel/latest/index.html) • [🔥 Ready-to-Use Recipes](https://github.com/NVIDIA-NeMo/Automodel/#supported-models) • [💡 Examples](https://github.com/NVIDIA-NeMo/Automodel/tree/main/examples) • [Model Coverage](https://docs.nvidia.com/nemo/automodel/latest/model-coverage/overview.html) • [Performance](https://docs.nvidia.com/nemo/automodel/latest/performance-summary.html) • [🤝 Contributing](https://github.com/NVIDIA-NeMo/Automodel/blob/main/CONTRIBUTING.md)
📣 News and Discussions
- [10/25/2026]Nanbeige4.3-33B Fine-tune Nanbeige's dense 33B agentic model on 128K packed sequences with context parallelism. See the model card. Explore the 128K SFT CP16 and 128K LoRA CP8 recipes.
- [10/23/2026]NVIDIA Nemotron 3.5 Bolt Fine-tune NVIDIA-Nemotron-3.5-Bolt-E4B-4GB-BF16 with the MedPix full-parameter SFT and MedPix LoRA recipes, and NVIDIA-Nemotron-3.5-Bolt-74B-A9B-BF16 with the CORD-v2 LoRA recipe. See the E4B and 74B-A9B model coverage pages.
- [10/23/2026]MiniMax-M3.1-Flash We now support fine-tuning MiniMax AI's MoE vision-language model, loading its NVFP4 and MXFP8 checkpoint directly. Check out the MedPix SFT EP128 recipe and the model coverage page.
- [10/21/2026]Flint Fine-tune Recursive's 39.8B-A2.5B MoE model with expert and context parallelism. See the model card. Explore the SFT, LoRA, 128K packed TE, and 128K packed MagiAttention (H100) recipes.
- [10/21/2026]EAGLE-4 We now support training EAGLE-4 drafters: the EAGLE-3.1 draft with a sliding-window layer and a low-rank candidate head over the full vocabulary, trained in two stages and exported to the
LlamaForCausalLMEagle4 serving layout, many thanks to @Khazic. Check out the Qwen3-8B draft and candidate-head recipes and the speculative decoding overview.
- [10/16/2026]Beam-1.0-501B-A23B We now support LoRA and full-parameter fine-tuning for Reflection AI's 501B-A23B sparse MoE with mixed sliding-window and full attention, using FSDP2, expert parallelism, and packed sequences. Check out the Tulu3 LoRA EP8 and Tulu3 SFT EP64 8-node recipes and the model coverage page.
- [10/15/2026]Muse Spark Open Fine-tune Meta's MoE model with expert, pipeline, and context parallelism. See the model card. Explore the image-text SFT, LoRA, and 128K long-context packed SFT recipes.
- [10/15/2026]NVIDIA Nemotron 3.5 Super VL Fine-tune the 120B-A12B vision-language model with CORD-v2 SFT, CORD-v2 PEFT (LoRA), 256K packed SFT (GB200). See the CORD-v2 tutorial for data preparation, training, and evaluation.
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[10/14/2026]Step-5-Preview-BF16 We now support StepFun's 600B-A27B sliding-window and sparse-attention MoE with FSDP2, expert, pipeline and context parallelism. Check out the model coverage page and the Tulu3 SFT, LoRA, and 128K long-context CP32 recipes.
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[10/12/2026]FLUX 3 Image Klein Base We added text-to-image and image-editing LoRA fine-tuning for Black Forest Labs' base image model. See the T2I LoRA recipe and model guide for checkpoint setup and the 100-step validation scope.
- [10/04/2026]HunyuanImage-3.0 We now support text-to-image full fine-tuning and LoRA for Tencent's 80B-A13B MoE multimodal decoder with FSDP2 and expert parallelism, many thanks to @Khazic. Check out the full fine-tuning and LoRA recipes and the model coverage page.
- [09/28/2026]Qwen-Image-2.1 We now support text-to-image full fine-tuning and LoRA for Qwen's 7B single-stream DiT conditioned on Qwen3-VL. Check out the full fine-tuning and LoRA recipes and the model coverage page.
- [09/26/2026]MiMo-V2.5-Pro We now support full-parameter fine-tuning for Xiaomi's hybrid full and sliding-window attention Mixture-of-Experts model from its FP8 checkpoint. Check out the [HellaSwag PP18/EP8