Alibaba Cloud ECS gn7i Instance Overview | Generated by AI
Question: How about this? Explain ecs.gn7i-c32g1.32xlarge in Alibaba Cloud ECS.
Answer:
ecs.gn7i-c32g1.32xlarge is a large-scale instance type from the gn7i GPU-accelerated compute-optimized instance family on Alibaba Cloud Elastic Compute Service (ECS).
Key Specifications
- vCPUs: 128
- Memory (System RAM): 752 GiB
- GPUs: 4 × NVIDIA A10 (Ampere architecture)
- GPU Memory: 24 GB per A10 GPU (total 96 GB GPU VRAM)
- CPU Processor: Intel Xeon Scalable (Ice Lake) Platinum 8369B processors, with base frequency of 2.9 GHz and all-core turbo up to 3.5 GHz
- Network Performance:
- Baseline bandwidth: 64 Gbit/s
- Packet forwarding rate: 24,000,000 PPS
- NIC queues: 32
- ENIs: 15
- Private IPv4 addresses per ENI: 30
- IPv6 addresses per ENI: 30
- Storage: I/O-optimized instance. No local disk included by default. Supports high-performance cloud disks such as ESSD, ESSD AutoPL, and Regional ESSD (you attach block storage as needed)
- Architecture: Built on Alibaba Cloud’s third-generation SHENLONG architecture with chip-level fast-path acceleration for improved storage, network, and computing stability
Naming Breakdown
- gn7i: GPU-accelerated compute-optimized family (gn = GPU, 7 = generation, i = Intel-based variant focused on inference and graphics)
- c32g1: Indicates the ratio/configuration – roughly 32 vCPUs per GPU in the base scaling (here scaled up to 128 vCPUs with 4 GPUs, so 32 vCPUs per GPU)
- .32xlarge: The size tier (largest in this particular c32g1 series line)
This gives a balanced high-density setup with a CPU-to-memory ratio of approximately 1:5.875 (more memory-heavy compared to standard compute instances).
Use Cases
This instance is optimized for:
- Concurrent AI inference workloads (e.g., image recognition, speech recognition, natural language processing, behavior identification)
- High-performance 3D graphics and virtualization tasks
- Remote graphic design, cloud gaming, or video rendering that benefits from NVIDIA RTX and TensorRT acceleration
- Scenarios needing strong CPU + large system memory alongside multiple GPUs
The NVIDIA A10 GPUs excel at inference and graphics rather than heavy training (for training, families like gn7e with larger 80 GB GPUs are often preferred).
Comparison to gn7t
Compared to the gn7t family (mentioned in your previous question):
- gn7i uses NVIDIA A10 GPUs (24 GB each) and is positioned for balanced inference + graphics.
- gn7t uses a different GPU variant (often listed as G39 in some references) and typically offers different system memory configurations per GPU in similar naming patterns.
- The ecs.gn7i-c32g1.32xlarge provides a very high total resource density (128 vCPU + 752 GiB RAM + 96 GB total GPU memory), making it suitable for large-scale concurrent workloads.
Pricing Note
Pricing varies significantly by region, payment method (on-demand, reserved, etc.), and commitment period. It is one of the higher-end GPU instances, so expect costs in the range of several USD per hour (check the Alibaba Cloud console for your specific region and current rates).
Recommendation
This is a powerful, high-end instance ideal when you need substantial parallel GPU capacity combined with lots of CPU cores and system memory. For smaller needs, consider lower tiers in the same family such as ecs.gn7i-c32g1.8xlarge (32 vCPU, 188 GiB, 1× A10) or ecs.gn7i-c32g1.16xlarge.
Always verify the latest specifications, availability, and exact pricing in your target region through the Alibaba Cloud ECS console or official documentation, as details can be region-specific and subject to updates.
References:
- Alibaba Cloud GPU-accelerated instance families documentation
- Alibaba Cloud ECS instance type details for gn7i
- Third-party spec references: Cloud Mercato and SpareCores listings for ecs.gn7i-c32g1.32xlarge