Baidu Baige Team
Baidu Baige (百度百舸) is a Baidu Intelligent Cloud AI-computing platform for large-scale deep-learning and foundation-model workflows. It provides cloud-native infrastructure and lifecycle tooling spanning resource preparation, model development, training, inference deployment, acceleration, fault tolerance and diagnostics, with the stated aim of simplifying AI infrastructure so enterprise customers can focus on business value. Sources: https://cloud.baidu.com/product/aihc.html ; https://cloud.baidu.com/article/3554310
At a Glance
- Enterprise AI and model-development teams
- Education
- Computer vision
- Embodied intelligence and robotics
- +5 more
AI Tools by Baidu Baige Team
(1)
LoongForge
Open Source LLM Training Framework
Discussions
No discussions yet
Be the first to start a discussion about Baidu Baige Team
Latest News
LoongForge announced the TAOT topology-aware expert-placement work, reporting 1.43x faster MoE training in a real case.
LoongForge-Embodied was released as a torch-native DDP/FSDP subsystem for embodied models, with the project page reporting up to 4.38x speedup.
Baige's official release log announced the new workflow module with YAML-based serial, parallel and diamond-shaped task orchestration.
The Baige release log recorded Guangzhou-region availability, embodied-AI RoboTwin 2.0 quick deployment, and broader workload/resource views.
Products & Services
Cloud-native heterogeneous AI-computing platform covering resource pools, development machines, distributed training, online inference/model deployment, storage, monitoring, scheduling, fault tolerance, diagnosis and full AI-engineering lifecycle management. Source: https://cloud.baidu.com/product/aihc.html ; https://cloud.baidu.com/doc/AIHC/s/dly5i8vfs
Acceleration tools and images for Megatron and Megatron-Core training and inference, model-weight conversion between Hugging Face and Megatron, parallel-strategy partitioning and automatic parallel-strategy search. It covers Llama, Qwen, Baichuan, Mixtral and other mainstream models. Source: https://cloud.baidu.com/doc/AIHC/s/0lqc6hxb
Apache-2.0 open-source training framework from the Baidu Baige GitHub organization for LLMs, VLMs, diffusion and embodied models. It provides ready-to-run configurations for 35+ model families, Megatron-LM and torch-native backends, NVIDIA GPU and Kunlun XPU support, and reported speedups up to about 5x. Sources: https://baidu-baige.github.io/LoongForge/ ; https://github.com/baidu-baige/LoongForge ; https://loongforge.readthedocs.io/en/latest/index.html
Market Position
Baige positions itself as an enterprise-grade, full-lifecycle AI infrastructure layer rather than only a model API: it combines heterogeneous cloud compute, storage, containers, cluster operations, training and inference acceleration, and production reliability. Its differentiators are Baidu's large-scale model-training experience, Kunlun XPU/GPU multi-chip support, AIAK optimization, high-scale fault tolerance and integrated training/inference. Relevant alternatives include hyperscaler GPU platforms such as Alibaba Cloud PAI and NVIDIA GPU Cloud, Kubernetes plus Kubeflow/Volcano stacks, and open training/serving frameworks such as Megatron-LM, vLLM and SGLang; Baige's stated advantage is tighter integration and managed operation across these layers. Sources: https://cloud.baidu.com/product/aihc.html ; https://cloud.baidu.com/article/3554310 ; https://cloud.baidu.com/doc/AIHC/s/0lqc6hxb
Leadership
Executive Team
王雁鹏 (Wang Yanpeng)
Baidu Intelligent Cloud AI Computing Chief Scientist
Presented the Baige 5.0 technical architecture at the 2025 Cloud Intelligence Conference and is identified by Baidu Intelligent Cloud as its AI-computing chief scientist. Source: https://cloud.baidu.com/article/3554310
Founding Story
Baidu Intelligent Cloud launched Baidu Baige in June 2021 as an AI infrastructure platform. Its initial architecture combined AI computing, AI storage and AI containers, drawing on Baidu's experience operating large-scale AI systems and supporting workloads such as Wenxin model training, autonomous-driving algorithms and life-sciences computing. Source: https://baike.baidu.com/item/%E7%99%BE%E5%BA%A6%E7%99%BE%E8%88%B8%20%C2%B7%20AI%E5%BC%82%E6%9E%84%E8%AE%A1%E7%AE%97%E5%B9%B3%E5%8F%B0/59276169
Business Model
Revenue Model
Cloud infrastructure consumption and paid AI-computing resources: Baige nodes (CPU, memory and GPU) and cloud disks are billed separately, with prepaid subscription and pay-as-you-go options; the platform also offers reserved-instance vouchers. Source: https://cloud.baidu.com/doc/AIHC/s/Xlidzpic2 ; https://cloud.baidu.com/doc/AIHC/s/Ymhxdyhkb
Pricing Tiers
Commitment periods range from 1–9 months or 1–5 years; described as cheaper than pay-as-you-go for stable long-term workloads. Source: https://cloud.baidu.com/doc/AIHC/s/Ymhxdyhkb
Charged by actual instance usage per minute, with hourly billing; the documentation says exact instance pricing requires contacting Baidu support. Source: https://cloud.baidu.com/doc/AIHC/s/Ymhxdyhkb
A commitment-based credit and capacity-reservation mechanism for qualifying pay-as-you-go nodes, described for terms such as 1 or 3 years. Source: https://cloud.baidu.com/doc/AIHC/s/Ymhxdyhkb
Target Markets
- Enterprise AI and model-development teams
- Education
- Computer vision
- Embodied intelligence and robotics
- Automotive and autonomous driving
- E-commerce
- Foundation-model pretraining, continued pretraining and SFT/LoRA fine-tuning
- Large-model inference and production model serving
- Multimodal and vision-language model development
- Embodied intelligence, VLA/WAM training, simulation and robotics
- Autonomous-driving model training and validation
- Generative AI and diffusion-model workloads
- Beijing Humanoid Robot Innovation Center — uses Baige for compute scheduling, model training/inference acceleration and an end-to-end embodied-AI development environment; Xinhua reported a 2x efficiency improvement. Source: https://www3.xinhuanet.com/tech/20250828/63a7344724ba400aabfb3eb429f74453/c.html
- Qianxun Intelligence — named on Baige's official product page as using the platform for embodied-model compute scheduling and training/inference acceleration. Source: https://cloud.baidu.com/product/aihc.html
- An unnamed computer-vision company — the official product page describes Kunlunxin P800 plus Baige being used to build secure, efficient AI infrastructure for government and finance deployments. Source: https://cloud.baidu.com/product/aihc.html
- Baidu Wenxin large model — Baige is described as supporting Wenxin model training at thousand-card scale. Source: https://baike.baidu.com/item/%E7%99%BE%E5%BA%A6%E7%99%BE%E8%88%B8%20%C2%B7%20AI%E5%BC%82%E6%9E%84%E8%AE%A1%E7%AE%97%E5%B9%B3%E5%8F%B0/59276169