Top GPU Cloud Providers in China | Generated by AI
Question: What are the top GPU cloud providers in China for training models like GPT-3?
Answer:
If you want to train GPT-3–style large language models, China’s GPU cloud market is mainly dominated by Alibaba / Huawei / Baidu / Tencent, plus a few newer GPU-only providers. These platforms offer A100/H100-class GPUs (or domestic alternatives like Ascend/Kunlun) and distributed training clusters.
🇨🇳 Top GPU cloud providers in China (for GPT-3 scale)
1. Alibaba Cloud (阿里云) — most commonly used
- GPUs: A100, V100, T4, some H800/H20 variants
- Supports: multi-node distributed training, RDMA networking
- Has PAI (Platform for AI) for large model training
- Large market share and most mature ecosystem
- Used by many Chinese LLM teams
Alibaba Cloud provides multi-GPU and distributed training environments suitable for deep learning and large models. (blog.27nk.com)
Best for:
- GPT-like training
- PyTorch / Megatron / DeepSpeed
- multi-node cluster training
2. Huawei Cloud (华为云) — strong for large-scale LLM
- GPUs: Ascend 910 / 910B (domestic AI chips)
- cluster scale: thousands of accelerators
- optimized for large model training
Huawei’s Ascend-based clusters emphasize dense clustering and high-speed interconnects to train large foundation models even without NVIDIA GPUs. (Tom’s Hardware)
Best for:
- Chinese LLM training
- long-running pretraining
- lower cost than NVIDIA sometimes
3. Baidu AI Cloud (百度智能云)
- GPUs: A100, V100 + Kunlun chips
- integrated with PaddlePaddle
- built large 30,000-chip training cluster
Baidu reported a 30,000-chip training cluster capable of hundreds-billion-parameter models, showing strong LLM training capability. (Tom’s Hardware)
Best for:
- PaddlePaddle ecosystem
- Chinese LLM stack
- large distributed training
4. Tencent Cloud (腾讯云)
- GPUs: A100 / V100 clusters
- internal GPT-scale training systems (Angel-PTM)
- supports Transformer pretraining at scale
Tencent’s large-model system successfully trained GPT-3-175B scale models using hundreds of GPUs, showing strong scalability. (arXiv)
Best for:
- PyTorch training
- transformer pretraining
- multi-node GPU cluster
5. GPU-native providers (cheaper / startup-friendly)
These are more like RunPod / Lambda but in China:
- Dataoorts GPU Cloud (H100/A100 clusters)
- RunPod (China regions)
- Gcore (Asia + China edge)
These platforms provide on-demand H100/A100 GPU clusters for AI training. (Dataoorts)
Best for:
- startups
- short training runs
- cheaper experimentation
Which one to choose (for GPT-3 training)
If your goal is train GPT-3 scale (100B+):
Best order:
- Alibaba Cloud — easiest & mature
- Huawei Cloud — large scale cheap compute
- Baidu AI Cloud — strong for Chinese ecosystem
- Tencent Cloud — good but less open
- GPU startups — cheapest but less stable
What you actually need (GPT-3 scale)
Typical compute:
- GPT-3 175B
- ~1000–8000 A100 GPUs
- InfiniBand / RDMA network
- weeks of training
China providers do support this, but usually:
- enterprise contract
- reservation required
- not self-serve UI
Cheapest realistic option in China (small team)
If you’re not OpenAI-level:
Use:
- 8–64 A100
- DeepSpeed / Megatron
- train 7B–70B model
That’s what most Chinese startups do.
If you tell me:
- budget (example: $5k / $50k / $500k)
- model size (7B / 70B / GPT-3)
- open source or from scratch
I can tell you exact cloud + GPU count.
References:
- https://dataoorts.com/top-10-cloud-gpu-providers-for-ai-and-deep-learning-in-china/
- https://www.tomshardware.com/tech-industry/chinas-gpu-cloud-consolidates-around-baidu-and-huawei-as-domestic-ai-chips-scale-up
- https://blog.27nk.com/article/9613
- https://dataoorts.com/top-5-plus-gpu-cloud-providers-in-china/
- https://arxiv.org/abs/2303.02868