Alibaba Cloud

Name: Alibaba Cloud GPU Cloud
Brand: Alibaba Cloud
Availability: InStock
Rating: 8.6 (83 reviews)

☁️ Hyperscalers

Large-scale Enterprise Deployment

🏢 Hangzhou, China📅 Since 2009★ 8.6/10🌐 Website ↗

Global Regions

30+

GPU Families

Spot Discount

Up to 90%

Min Commitment

On-demand

GDPR ISO BSI PCI-DSS Multi-Tier Cloud Security

The Asian Cloud Giant

Alibaba Cloud (Aliyun) is the undisputed leader in cloud computing across the Asia-Pacific region and the backbone of the massive Alibaba e-commerce ecosystem. Its Apsara AI infrastructure is engineered to handle some of the highest-throughput computational events in the world (such as Singles’ Day). For AI, Alibaba offers high-end instances equipped with NVIDIA A100 and A800 GPUs, linked by custom eRDMA (Elastic RDMA) networks that deliver 400 Gbps of bandwidth for seamless distributed training.

Qwen and the Model Studio

Alibaba has aggressively entered the Generative AI race with its open-source Tongyi Qianwen (Qwen) models. Through the Alibaba Cloud DashScope platform, enterprises can access these powerful multi-lingual foundation models via API. For custom deployments, Alibaba’s Model Studio provides a comprehensive toolchain to fine-tune and orchestrate LLM agents, heavily optimized for the Chinese language and regional business nuances.

Platform for AI (PAI)

Alibaba’s Platform for AI (PAI) is a fully managed machine learning suite that accelerates the entire AI lifecycle. PAI includes deep hardware optimization layers that can accelerate PyTorch and TensorFlow training times by up to 30%. With native integration into Alibaba’s Cloud Container Service for Kubernetes (ACK), enterprises can easily deploy highly scalable, auto-healing AI inference clusters.

Pros & Cons

Pros

Largest footprint in Asia Pacific
PAI framework optimizations
Tongyi Qianwen (Qwen) foundation models
eRDMA high-speed networking

Cons

Geopolitical data restrictions
Complex international billing
Latency outside of Asian nodes

Managed ML Platform Services

Alibaba Cloud offers high-level platform services (PaaS) to streamline model lifecycle management, including: Platform for AI (PAI), DashScope, Model Studio. Ideal for enterprise MLOps, managed training, and automated endpoint deployment without managing raw infrastructure.

GPU Hardware Families

A100

Available for Compute

V100

Available for Compute

A10

Available for Compute

Specific Instance Types

A100V100T4A10

Hyperscaler instance types dictate the ratio of GPU, vCPU, RAM, and network bandwidth. Search the provider's instance catalog to match your exact bottleneck (compute-bound vs memory-bound vs I/O-bound).

Enterprise Architecture & Ecosystem

High-Speed Interconnects

eRDMA (Elastic RDMA) network interface delivers up to 400 Gbps bandwidth per node, engineered specifically to accelerate large language model (LLM) training and distributed deep learning across Alibaba's Apsara AI clusters.

Parallel Storage Systems

Cloud Parallel File System (CPFS) provides tens of millions of IOPS and sub-millisecond latency. CPFS integrates seamlessly with Alibaba OSS to feed exabytes of data directly to NVIDIA H100 and A800 GPU clusters.

Managed Kubernetes (K8s)

Alibaba Cloud Container Service for Kubernetes (ACK) offers specialized AI node pools, GPU sharing capabilities, and native integration with Alibaba's PAI (Platform for AI) for full-lifecycle MLOps.

Data Egress Strategy

Outbound data transfer is charged per GB, starting at approximately $0.07/GB. Alibaba Cloud Express Connect establishes dedicated physical connections to bypass public internet congestion and lower enterprise transfer fees.

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Official Hardware Catalog

For the most accurate GPU availability, memory specifications (e.g., A100 40GB vs 80GB), and network interconnect speeds (InfiniBand vs standard Ethernet), check the official compute dashboard.

View full instance specs →

Enterprise Procurement Models

Hyperscaler pricing is notoriously complex. You pay for compute (instances), but also for storage, data egress, and premium support. Choosing the right commitment model is critical.

On-Demand

No long-term commitment. Pay by the hour or second. Highest flexibility but highest cost. Best for unpredictable or spiky workloads.

Reserved Instances

Commit to a specific instance family in a specific region for 1 or 3 years. Discount ranges from 30% to 72% off on-demand rates.

Spot / Preemptible

Bid on spare capacity. Massive discounts (up to 90%) but instances can be terminated with 2 minutes notice. Best for fault-tolerant batch jobs.