Alibaba Cloud
ecs.gn5-c8g1.14xlarge
x86 · ecs.gn5Alibaba Cloud 54 vCPU / 480 GiB · NVIDIA P100 ×8 · 16GB · x86 · in 11 regions.
Specs & pricing
Total /mo $11,279/mo
Compute /mo $11,277/mo
40G disk $2.6/mo
per vCPU/mo $209 per GiB/mo $24 per GPU/mo $1,410 Reserved saves up to 83.5% Spot saves up to 56.5%
vCPU54
Memory480 GiB
Archx86
GPUNVIDIA P100 ×8 · 16GB
Bandwidth25 Gbps
40G diskSSD · +$2.6/mo
Regions11
Familyecs.gn5
Total · incl. 40G disk
| By billing type | Min/mo | Avg/mo | Max/mo | Regions |
|---|---|---|---|---|
| On-demand | $11,279 | $12,803 | $13,346 | 11 |
| Monthly | $4,740 | $6,140 | $8,713 | 11 |
| Spot | $2,004 | $5,558 | $6,674 | 10 |
| Reserved | $1,661 | $2,117 | $3,313 | 11 |
Same spec on other clouds
No same-spec instance found on other clouds.
Price by region · Total · incl. 40G disk
| 🇺🇸 N. Virginia us-east-1 | $11,279 | $7,047 | $5,641 | $2,227 |
| 🇨🇳 Hohhot cn-huhehaote | $12,012 | $4,740 | $2,404 | $1,661 |
| 🇨🇳 Zhangjiakou cn-zhangjiakou | $12,012 | $4,740 | $6,007 | $1,661 |
| 🇺🇸 Silicon Valley us-west-1 | $12,407 | $7,752 | $6,205 | $2,450 |
| 🇮🇩 Jakarta ap-southeast-5 | $13,143 | $8,212 | — | $2,595 |
| 🇯🇵 Tokyo ap-northeast-1 | $13,249 | $8,713 | $6,626 | $3,313 |
| 🇨🇳 Beijing cn-beijing | $13,346 | $5,267 | $2,004 | $1,845 |
| 🇨🇳 Hangzhou cn-hangzhou | $13,346 | $5,267 | $6,674 | $1,845 |
| 🇨🇳 Shanghai cn-shanghai | $13,346 | $5,267 | $6,674 | $1,845 |
| 🇨🇳 Shenzhen cn-shenzhen | $13,346 | $5,267 | $6,674 | $1,845 |
| 🇨🇳 Ulanqab cn-wulanchabu | $13,346 | $5,267 | $6,674 | $2,003 |
All are the total monthly price = machine (effective hourly ×730) + a 40G system disk (~$2.6/mo, representative SSD estimate): the lowest total per billing type per region. Normalized to USD — verify on each cloud's official page.
FAQ
How much does ecs.gn5-c8g1.14xlarge cost on Alibaba Cloud?
ecs.gn5-c8g1.14xlarge runs from about $11,279/mo (Linux on-demand + a 40G system disk), based on its cheapest of 11 regions.
Is ecs.gn5-c8g1.14xlarge cheaper on another cloud?
No same-spec instance was found on other clouds in our dataset.