Deploy APAC inference APIs near regional users. Compare GPU VRAM, model precision, storage and network paths; confirm data-location and contractual requirements for your workload.
Compare GPU models, memory, storage and network options to find a server for your compute workload.
USD 264.00/mo
Configure serverPrices below cover the full billing period, not a single month.
USD 286.00/mo
Configure serverPrices below cover the full billing period, not a single month.
USD 330.00/mo
Configure serverPrices below cover the full billing period, not a single month.
USD 748.00/mo
Configure serverPrices below cover the full billing period, not a single month.
Prices are for the configurations shown. Confirm your configuration, total price and availability before placing an order.
Why Choose POWOKE Hong Kong GPU Server
A regional base for applications serving Hong Kong and Asia Pacific; assess China-facing routes separately from international traffic.
Size AI inference, training and rendering around GPU memory, software compatibility and job duration. Compare available hardware and billing options.
Verify image versions, licensing and administration access against the application you intend to run.
Include renewal terms, data transfer, additional IPs, software licenses and backup requirements in the total cost.
Confirm maintenance windows, restart requirements and recovery steps before scaling or migrating production workloads.
Include the service ID, timestamps, logs and network test results to help distinguish infrastructure from application issues.
Enterprise-grade infrastructure, low latency network
Availability is governed by the product SLA, measurement method and exclusions. Measure latency and performance from your own environment.
20-100Mbps dedicated bandwidth, supports large dataset upload and download, fast model distribution
Internationally certified data center, 99.9% power guarantee, professional cooling system, stable GPU operation
Encrypted data transmission, regular backups, compliant with data security standards, protecting AI models and data
Covering AI, rendering and other mainstream applications
Deep learning model training, neural network optimization, large-scale data processing
Image recognition, natural language processing, recommendation systems and other ML applications
3D modeling, animation rendering, ray tracing, visual effects production
Video transcoding, real-time encoding, AI video enhancement, live streaming
Molecular simulation, climate prediction, gene sequencing and other high-performance computing
Big data analytics, data mining, business intelligence BI applications
Hong Kong GPU Server Complete Technical Specifications
Hong Kong GPU Server FAQ Answers
Start with model or scene memory, precision and concurrency. Then check GPU architecture, CPU capacity, system RAM and data-loading performance.
Use the billing options shown for the selected configuration. Confirm minimum charges, what happens when a job stops and the cost of long-running tasks.
Check the billing term, transfer allowance, IP allocation, software licensing and renewal conditions. Available payment methods are shown at checkout.
Upgrade procedures depend on the product and resource. Confirm whether a change requires a restart, migration or disk reconfiguration, and keep a tested backup before making changes.
Test from the networks your customers use, including peak periods. Consider latency, packet loss, return paths and the locations of databases, backups and external services.
Available images vary by node and plan. Check the version, licensing, access method and application compatibility in the configuration flow before ordering.
Practical guidance on server selection, deployment and everyday operations.
Explore city-to-city latency across public and private backbone networks.
| From / To | HKG | TYO | SIN | FRA | LON | LAX | SYD | SAO |
|---|---|---|---|---|---|---|---|---|
| Hong Kong (HKG) | — | 49 | 39 | 221 | 225 | 147 | 274 | 320 |
| Tokyo (TYO) | 49 | — | 68 | 228 | 242 | 99 | 252 | 266 |
| Singapore (SIN) | 39 | 68 | — | 161 | 231 | 169 | 224 | 341 |
| Frankfurt (FRA) | 221 | 228 | 161 | — | 13 | 139 | 320 | 217 |
| London (LON) | 225 | 242 | 231 | 13 | — | 125 | 280 | 191 |
| Los Angeles (LAX) | 147 | 99 | 169 | 139 | 125 | — | 145 | 175 |
| Sydney (SYD) | 274 | 252 | 224 | 320 | 280 | 145 | — | 319 |
| São Paulo (SAO) | 320 | 266 | 341 | 217 | 191 | 175 | 319 | — |
No matching cities. Change the search or region.
Public network reference snapshot: values are the past-24-hour averages published at capture time. This is not a live test. Snapshot date: 2026-10-13.
Available gateways, settlement currency and fees depend on the final checkout. Review the billing term and total before paying.
Refund windows, transfer limits, refund destination and eligibility for 99.9% availability compensation depend on your order's service terms. Confirm whether a first-order 24-hour refund applies before purchase; custom hardware and GPU plans may have different rules.
Confirm service termsA practical handover checklist, from sizing the instance to moving live traffic.
Start with model size, precision, context and batch size. For multi-GPU jobs, verify device count, allocation and the actual interconnect.
Check driver, CUDA and framework compatibility. Run a small inference or rendering job before importing the full dataset.
Record time to first token, tokens per second, peak VRAM or batch render time on representative inputs. Include retries in job estimates.
Confirm charges when stopped, released or retaining disks. Export models, workflow files and outputs before terminating the instance.
Start with your model and workload, then validate memory usage, concurrency and the delivered software environment.
Hardware reference: RTX 4090 24GB GDDR6X; RTX 3090 24GB; A10 24GB; A30 24GB; A100 40GB/80GB HBM2e; H100 80GB HBM3. Available models, allocation and topology depend on the selected configuration.
Specify Ubuntu 22.04/24.04, NVIDIA driver, CUDA, cuDNN, PyTorch and TensorFlow versions when ordering. Verify the delivered image with nvidia-smi and a minimal inference run. The report’s RTX 4090 cost reference is $1.20/hour; confirm the actual hourly offer before estimating a job.
Confirm resources, renewal costs, payment options and delivery timing. Request a product-specific test IP and check routes from your users’ networks.
Match CPU, RAM, storage, IPs and OS to your order. Verify login, remote management access and connectivity.
Run a representative workload and test backup recovery. Save your results and open a support ticket if the delivered configuration differs.