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cuichenx merged 9 commits into from
Oct 9, 2026
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refactor(recipe)!: flatten Nemotron example directories #6371

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e77129a
refactor(recipe)!: flatten Nemotron example directories
cuichenx Oct 9, 2026
c3f63b0
Attach NVSkills validation signatures
svc-nvskills-signing Oct 9, 2026
f98d5fc
docs(recipe): use canonical Nemotron model order
cuichenx Oct 9, 2026
ad4b24f
Attach NVSkills validation signatures
svc-nvskills-signing Oct 9, 2026
5dd4bb0
fix(tests): add missing Nemotron layout copyright header
cuichenx Oct 9, 2026
8919acf
Attach NVSkills validation signatures
svc-nvskills-signing Oct 9, 2026
e289c9f
fix(tests): repair Nemotron paths and CI discovery
cuichenx Oct 9, 2026
03303a7
Attach NVSkills validation signatures
svc-nvskills-signing Oct 9, 2026
7c09d64
chore: merge main into Nemotron examples layout branch
cuichenx Oct 9, 2026
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10 changes: 5 additions & 5 deletions README.md
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## 📣 News
- [08/19/2026] **Megatron Bridge 0.6.0 released!** Highlights include GLM-5.2 with cuDNN fused DSA for 128K THD-packed context-parallel training, new LLM/VLM/diffusion models, more reliable VLM data and sequence packing, improved checkpoint and LoRA workflows, unified training and conversion launchers, and refreshed performance recipes. Huge thanks to our community contributors! See the [full release notes](https://github.com/NVIDIA-NeMo/Megatron-Bridge/releases/tag/v0.6.0).

- [08/11/2026] **NVIDIA Nemotron 3.5 Lightning is released!** Read the technical blog [here](https://developer.nvidia.com/blog/nvidia-nemotron-3-5-lightning-delivers-fast-accurate-specialized-task-execution-for-long-running-agents/). See the [Nemotron 3.5 Lightning README](https://github.com/NVIDIA-NeMo/Megatron-Bridge/blob/main/examples/models/nemotron/nemotron_3/lightning/README.md) for details.
- [08/11/2026] **NVIDIA Nemotron 3.5 Lightning is released!** Read the technical blog [here](https://developer.nvidia.com/blog/nvidia-nemotron-3-5-lightning-delivers-fast-accurate-specialized-task-execution-for-long-running-agents/). See the [Nemotron 3.5 Lightning README](https://github.com/NVIDIA-NeMo/Megatron-Bridge/blob/main/examples/models/nemotron/nemotron_3_5_lightning/README.md) for details.

- [07/31/2026] **[K-EXAONE-2](https://huggingface.co/LGAI-EXAONE/K-EXAONE-2.0-750B-A37B) is now supported**! Day-0 support for LG AI Research's K-EXAONE-2 (750B-A37B MoE) is now available on the [k-exaone-2 branch](https://github.com/NVIDIA-NeMo/Megatron-Bridge/tree/k-exaone-2). Users can convert checkpoints, run inference, fine-tune with SFT or PEFT (LoRA), and use the NVFP4 inference-optimized checkpoint released alongside the model. See the branch documentation for setup instructions and examples.

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- [05/20/2026] [**DeepSeek V4**](https://github.com/NVIDIA-NeMo/Megatron-Bridge/tree/main/examples/models/deepseek_v4) is now merged on **main**! See the [examples README](https://github.com/NVIDIA-NeMo/Megatron-Bridge/blob/main/examples/models/deepseek_v4/README.md) for conversion and inference details.

- [05/20/2026] [**Nemotron-3 Nano Omni**](https://huggingface.co/nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16) day-0 branch support is now merged on **main**! The 30B-A3B MoE multimodal model supports image, video, audio, and text workflows with checkpoint conversion, inference, SFT, and PEFT (LoRA) examples. Read the [NVIDIA Blog](https://blogs.nvidia.com/blog/nemotron-3-nano-omni-multimodal-ai-agents/) and see the [examples README](https://github.com/NVIDIA-NeMo/Megatron-Bridge/blob/main/examples/models/nemotron/nemotron_3_omni/README.md) for the full walkthrough.
- [05/20/2026] [**Nemotron-3 Nano Omni**](https://huggingface.co/nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16) day-0 branch support is now merged on **main**! The 30B-A3B MoE multimodal model supports image, video, audio, and text workflows with checkpoint conversion, inference, SFT, and PEFT (LoRA) examples. Read the [NVIDIA Blog](https://blogs.nvidia.com/blog/nemotron-3-nano-omni-multimodal-ai-agents/) and see the [examples README](https://github.com/NVIDIA-NeMo/Megatron-Bridge/blob/main/examples/models/nemotron/nemotron_3_nano_omni/README.md) for the full walkthrough.

- [05/19/2026] [**Nemotron-Labs Diffusion**](https://github.com/NVIDIA-NeMo/Megatron-Bridge/tree/main/examples/models/nemotron_labs_diffusion) is now supported on **main** with autoregressive-to-diffusion conversion, continuous pretraining, checkpoint conversion, and inference workflows. Read the [NVIDIA Research blog](https://research.nvidia.com/publication/2026-05_nemotron-labs-diffusion-tri-mode-language-model-unifying-autoregressive) for the tri-mode language model overview.

- [05/06/2026] [**Gemma 4 VL 26B-A4B**](https://github.com/NVIDIA-NeMo/Megatron-Bridge/tree/main/examples/models/gemma/gemma4_vl) is now supported! Checkpoint conversion, SFT, and PEFT (LoRA) recipes for Google's MoE vision-language model (26B total / 4B active params, 128 experts top-k=8, dual sliding/global attention with K=V tying on full-attention layers) are available on **main**. See the [examples README](https://github.com/NVIDIA-NeMo/Megatron-Bridge/blob/main/examples/models/gemma/gemma4_vl/README.md) for the full walkthrough.

- [04/28/2026] Day 0 support for [**Nemotron-3 Nano Omni**](https://huggingface.co/nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16), a 30B-A3B MoE multimodal model that jointly processes image, video, audio, and text. Checkpoint conversion, SFT, and LoRA recipes are available on **main** — see the [examples README](https://github.com/NVIDIA-NeMo/Megatron-Bridge/blob/main/examples/models/nemotron/nemotron_3_omni/README.md) for the full walkthrough.
- [04/28/2026] Day 0 support for [**Nemotron-3 Nano Omni**](https://huggingface.co/nvidia/Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16), a 30B-A3B MoE multimodal model that jointly processes image, video, audio, and text. Checkpoint conversion, SFT, and LoRA recipes are available on **main** — see the [examples README](https://github.com/NVIDIA-NeMo/Megatron-Bridge/blob/main/examples/models/nemotron/nemotron_3_nano_omni/README.md) for the full walkthrough.

- [04/19/2026] [**Qwen3.6-35B-A3B**](https://huggingface.co/Qwen/Qwen3.6-35B-A3B) is now supported! Qwen3.6 uses the same architecture as Qwen3.5 VL MoE (`Qwen3_5MoeForConditionalGeneration`) and works with the existing [Qwen3.5-VL bridge](https://github.com/NVIDIA-NeMo/Megatron-Bridge/tree/main/src/megatron/bridge/models/qwen_vl) out of the box — no code changes needed. HF→Megatron conversion and inference verified.

Expand All @@ -55,13 +55,13 @@

- [03/31/2026] **Agent Skills for Megatron Bridge!** We've added a [`skills/`](https://github.com/NVIDIA-NeMo/Megatron-Bridge/tree/main/skills) directory with structured guides that AI coding agents (Cursor, Claude Code, Codex, etc.) can use to help you add model support, set up dev environments, tune performance, and more. Try them out, and PRs to improve or add new skills are very welcome!

- [03/26/2026] [**Nemotron 3 Super**](https://github.com/NVIDIA-NeMo/Megatron-Bridge/tree/main/examples/models/nemotron/nemotron_3) is now on **main**! Checkpoint conversion and SFT/LoRA recipes (120B-A12B) are available in the main branch. Read the [blog post](https://developer.nvidia.com/blog/introducing-nemotron-3-super-an-open-hybrid-mamba-transformer-moe-for-agentic-reasoning/).
- [03/26/2026] [**Nemotron 3 Super**](https://github.com/NVIDIA-NeMo/Megatron-Bridge/tree/main/examples/models/nemotron) is now on **main**! Checkpoint conversion and SFT/LoRA recipes (120B-A12B) are available in the main branch. Read the [blog post](https://developer.nvidia.com/blog/introducing-nemotron-3-super-an-open-hybrid-mamba-transformer-moe-for-agentic-reasoning/).

- [03/12/2026] **Deprecating Python 3.10 support:** We're officially dropping Python 3.10 support with the upcoming 0.4.0 release. Downstream applications must raise their lower boundary to 3.12 to stay compatible with Megatron-Bridge.

- [12/16/2025] [Mind Lab](https://alpha.macaron.im/mindlab) successfully used Megatron-bridge and [VeRL](https://github.com/volcengine/verl) to trained GRPO Lora for Trillion-parameter model on 64 H800 - See their [techblog](https://alpha.macaron.im/mindlab/research/building-trillion-parameter-reasoning-rl-with-10-gpus).

- [12/15/2025] Day 0 support for [NVIDIA-NeMotron-3-Nano-30B-A3B-FP8](https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8)! [Reproducible code](https://github.com/NVIDIA-NeMo/Megatron-Bridge/tree/main/examples/models/nemotron/nemotron_3/nano) and custom NGC container: [nvcr.io/nvidia/nemo:25.11.nemotron_3_nano](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/nemo?version=25.11.nemotron_3_nano)
- [12/15/2025] Day 0 support for [NVIDIA-NeMotron-3-Nano-30B-A3B-FP8](https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8)! [Reproducible code](https://github.com/NVIDIA-NeMo/Megatron-Bridge/tree/main/examples/models/nemotron/nemotron_3_nano) and custom NGC container: [nvcr.io/nvidia/nemo:25.11.nemotron_3_nano](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/nemo?version=25.11.nemotron_3_nano)

## Overview

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