ecs.g5ne.4xlarge by Alibaba Cloud

ecs.g5ne.4xlarge is a ecs.g5ne family (16 vCPUs, 64 GiB RAM, 0 GB storage) server offered by Alibaba Cloud with 16 vCPUs, 64 GiB of memory and 0 GB of storage. The pricing starts at 0.09 USD per hour.
16 vCPU
64 GiB Memory
Spare SCore
11,738
(All-cores)
1,107
(Single-core)

Specifications

Server Metadata

Vendor ID
alicloud
Name
ecs.g5ne.4xlarge
Description
ecs.g5ne family (16 vCPUs, 64 GiB RAM, 0 GB storage)
Family
ecs.g5ne
Hw Virt
Status
active
Observed At
2026-10-05T08:52:39.830347

Availability

REGION / IDSPOTONDEMAND
Virginia (US) / us-east-1
0.09 USD/h 0.9 USD/h
Manila (PH) / ap-southeast-6
0.1984 USD/h 1.044 USD/h
London (GB) / eu-west-1
0.22 USD/h 1.1 USD/h
Jakarta (ID) / ap-southeast-5
0.2088 USD/h 1.16 USD/h
Hong Kong (HK) / cn-hongkong
0.2204 USD/h 1.16 USD/h
Frankfurt (DE) / eu-central-1
0.2668 USD/h 1.16 USD/h
Ulanqab (CN) / cn-wulanchabu
0.2774 USD/h 1.206 USD/h
Hohhot (CN) / cn-huhehaote
0.2295 USD/h 1.208 USD/h
Tokyo (JP) / ap-northeast-1
0.1952 USD/h 1.22 USD/h
Heyuan (CN) / cn-heyuan
0.1206 USD/h 1.34 USD/h
Guangzhou (CN) / cn-guangzhou
0.2278 USD/h 1.34 USD/h
Qingdao (CN) / cn-qingdao
0.2345 USD/h 1.34 USD/h
Shenzhen (CN) / cn-shenzhen
0.2144 USD/h 1.34 USD/h
Shanghai (CN) / cn-shanghai
0.2546 USD/h 1.34 USD/h
Beijing (CN) / cn-beijing
- 1.34 USD/h
Chengdu (CN) / cn-chengdu
- 1.34 USD/h
Hangzhou (CN) / cn-hangzhou
- 1.34 USD/h

Processor

vCPUs
16
Hypervisor
KVM
CPU Allocation
Dedicated
CPU Cores
8
CPU Speed
2.5 GHz
CPU Architecture
x86_64
CPU Manufacturer
Intel
CPU Family
Xeon
CPU Model
8163
CPU L1D Cache
32 KiB
CPU L1D Cache Total
256 KiB
CPU L1I Cache
32 KiB
CPU L1I Cache Total
256 KiB
CPU L2 Cache
1 MiB
CPU L2 Cache Total
8 MiB
CPU L3 Cache
33 MiB
CPU L3 Cache Total
33 MiB
CPU Flags
fpu, vme, de, pse, tsc, msr, pae, mce, cx8, apic, sep, mtrr, pge, mca, cmov, pat, pse36, clflush, mmx, fxsr, sse, sse2, ss, ht, syscall, nx, pdpe1gb, rdtscp, lm, constant_tsc, rep_good, nopl, xtopology, nonstop_tsc, cpuid, tsc_known_freq, pni, pclmulqdq, ssse3, fma, cx16, pcid, sse4_1, sse4_2, x2apic, movbe, popcnt, tsc_deadline_timer, aes, xsave, avx, f16c, rdrand, hypervisor, lahf_lm, abm, 3dnowprefetch, pti, ibrs, ibpb, stibp, fsgsbase, tsc_adjust, bmi1, hle, avx2, smep, bmi2, erms, invpcid, rtm, mpx, avx512f, avx512dq, rdseed, adx, smap, avx512cd, avx512bw, avx512vl, xsaveopt, xsavec, xgetbv1, arat
Ecpus
10.6
Scalability
66.25

System Resources and Accelerators

MEMORY
Memory Amount
64 GiB
Memory Amount Actual
64 GiB
GPU
GPU Count
0
GPU Memory Min
0 MiB
GPU Memory Total
0 MiB
GPUs
    STORAGE
    Storage Size
    0 GB
    Storages
      NETWORK
      Network Speed Baseline
      7 Gbps
      Inbound Traffic
      0 GB/month
      Outbound Traffic
      0 GB/month
      IPv4
      0

      CPU and System Topology

      Server Description

      A dedicated general-purpose virtual server offering balanced compute and memory resources for multi-threaded enterprise applications and web serving.

      General Purpose

      Alibaba Cloud ecs.g5ne.4xlarge is an x86_64 general-purpose instance powered by the KVM hypervisor. It features 16 dedicated vCPUs derived from 8 physical Intel Xeon 8163 cores running at 2.5 GHz, paired with 64.0 GB of RAM. The hardware configuration lacks local storage and GPU accelerators, relying on a 7 Gbps baseline network bandwidth. Benchmark data reveals weak single-core CPU and memory performance, but average multi-core processing, software compilation, and database operation capabilities. This resource profile makes the instance suitable for multi-threaded workloads such as static web serving, Redis deployments, and general-purpose application hosting where dedicated CPU allocation is required but extreme single-thread speed is not critical.

      Economics

      Average Price per Region

      Prices per Zone

      Lowest Prices

      Performance

      Workload Profiles

      0.58Score
      Precomputed compound score for Cache Intensive workloads. A weighted average (geometric mean) of benchmark scores compared to their medians: score = ∏ (x_i / m_i)^(w_i / Σw). The score of 1.0 represents a synthetic baseline server with the median performance of each component benchmark; 0.5 means roughly half the performance; and 2.0 means twice the performance of that reference profile. Component weights: 50% Redis RPS (pipeline=1, SET), 20% Redis RPS (pipeline=16, SET), 10% PassMark Memory Mark (composite), 10% Memory bandwidth (read, 16 MB ~ L3), 10% PassMark single-thread CPU. Rationale for component selection: In-memory key-value store workload, mixing direct Redis performance metrics with memory speed and latency benchmarks, and single-core CPU performance profiles.
      Component Score Weight Impact
      Raw Reference Normalized Target Actual
      Redis RPS (pipeline=1, SET) 957,342 ops/sec 1,916,704 ops/sec 0.51 50.00% 50.00% -29.00%
      Redis RPS (pipeline=16, SET) 6,893,436 ops/sec 11,642,227 ops/sec 0.57 20.00% 20.00% -11.00%
      PassMark Memory Mark (composite) 1,757 2,417 0.75 10.00% 10.00% -2.80%
      Memory bandwidth (read, 16 MB ~ L3) 75,271 MB/sec 108,361 MB/sec 0.68 10.00% 10.00% -3.80%
      PassMark single-thread CPU 1,689 Mops/s 2,365 Mops/s 0.71 10.00% 10.00% -3.40%

      Memory Bandwidth

      Compression

      OpenSSL

      Geekbench Single-Core

      Score: 949

      Geekbench Multi-Core

      Score: 5,846

      Passmark CPU Scores

      BENCHMARKSCORE
      Mark
      		 12951
      Compression
      		 181791
      Encryption
      		 5434
      Extended Instructions
      		 11904
      Floating Point Maths
      		 21061
      Integer Maths
      		 39256
      Physics
      		 1254
      Prime Numbers
      		 67
      Single Threaded
      		 1689
      String Sorting
      		 23894

      Passmark Memory Scores

      BENCHMARKSCORE
      Memory Mark
      		 1757
      Database Operations
      		 4307
      Memory Latency
      		 80
      Memory Read Cached
      		 19482
      Memory Read Uncached
      		 6435
      Memory Write
      		 6875

      Stress-ng Raw Scores

      Stress-ng Relative Multicore Performance

      LLM Inference Speed for Prompt Processing

      LLM Inference Speed for Text Generation

      Static Web Server

      Redis

      Alternatives

      Servers of the Same Family

      INSTANCEvCPUsMEMORYGPUs
      ecs.g5ne.large 28 GiB0
      ecs.g5ne.xlarge 416 GiB0
      ecs.g5ne.2xlarge 832 GiB0
      ecs.g5ne.8xlarge 32128 GiB0
      ecs.g5ne.16xlarge 64256 GiB0
      ecs.g5ne.18xlarge 72288 GiB0

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      ecs.g5ne.4xlarge FAQs