LoongForge-A high-performance training framework for LLM, VLM, DIT, VLA models
LoongForge is a high-performance training framework designed for various AI models, including LLMs and VLMs. It offers significant speed improvements and supports both NVIDIA GPUs and Kunlun XPUs. The framework is part of Baidu Baige's open-source series and aims to enhance training efficiency across multiple domains.
- ▪LoongForge provides up to 5.04× training speedup compared to mainstream open-source baselines.
- ▪It supports production training for enterprise customers in sectors like Education and Computer Vision.
- ▪The framework includes features like flexible multi-modal composition and heterogeneous parallelism.
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Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/baidu-baige/LoongForge |
| Publication time | Wed, 27 May 2026 17:58:08 +0000 |
| Retrieval time | 2026-05-27T18:08:02.537Z |
| Last seen | 2026-05-27T18:08:02.537Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | k3ajcBqFf3a- |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
English | 中文 A modular, scalable, high-performance training framework for LLMs, VLMs, diffusion, and embodied models. 🚀 Up to 5.04× training speedup · 🌐 Native NVIDIA GPU & Kunlun XPU support 💡 Why LoongForge? 🐉 LoongForge is part of Baidu Baige's Loong open-source series — named after the traditional Chinese loong boat (龙舟), a symbol of coordinated power and forward momentum. LoongForge is a unified training framework for LLMs, VLMs, VLAs, and diffusion models, covering pre-training, continued pre-training, and SFT. Built upon Megatron-LM with deep systemic enhancements across model coverage, training performance, and hardware support, it delivers significant speedups over mainstream open-source baselines.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.