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ecs.g8ae.8xlarge by Alibaba Cloud

ecs.g8ae.8xlarge is a ecs.g8ae family (32 vCPUs, 128 GiB RAM, 0 GB storage) server offered by Alibaba Cloud with 32 vCPUs, 128 GiB of memory and 0 GB of storage. The pricing starts at 0.5996 USD per hour.
32 vCPU
128 GiB Memory
Spare SCore
49860
(All-cores)
3114
(Single-core)

Specifications

Server Metadata

Vendor ID
alicloud
Name
ecs.g8ae.8xlarge
Description
ecs.g8ae family (32 vCPUs, 128 GiB RAM, 0 GB storage)
Family
ecs.g8ae
Hw Virt
Average Time To Start
12
Status
active
Observed At
2026-08-03T07:07:57.687062

Availability

REGION / IDSPOTONDEMAND
Beijing (CN) / cn-beijing
0.5996 USD/h 1.4276 USD/h
Shanghai (CN) / cn-shanghai
- 1.4276 USD/h

Processor

vCPUs
32
Hypervisor
KVM
CPU Allocation
Dedicated
CPU Cores
32
CPU Speed
3.4 GHz
CPU Architecture
x86_64
CPU Manufacturer
AMD
CPU Family
EPYC
CPU Model
9T34
CPU L1D Cache
32 KiB
CPU L1D Cache Total
512 KiB
CPU L1I Cache
32 KiB
CPU L1I Cache Total
512 KiB
CPU L2 Cache
1 MiB
CPU L2 Cache Total
16 MiB
CPU L3 Cache
32 MiB
CPU L3 Cache Total
64 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, ht, syscall, nx, mmxext, fxsr_opt, pdpe1gb, rdtscp, lm, constant_tsc, rep_good, amd_lbr_v2, nopl, nonstop_tsc, cpuid, extd_apicid, aperfmperf, tsc_known_freq, pni, pclmulqdq, monitor, ssse3, fma, cx16, pcid, sse4_1, sse4_2, x2apic, movbe, popcnt, aes, xsave, avx, f16c, rdrand, hypervisor, lahf_lm, cmp_legacy, extapic, cr8_legacy, abm, sse4a, misalignsse, 3dnowprefetch, osvw, ibs, topoext, perfctr_core, perfctr_llc, mwaitx, ssbd, perfmon_v2, ibrs, ibpb, stibp, ibrs_enhanced, vmmcall, fsgsbase, tsc_adjust, bmi1, avx2, smep, bmi2, erms, invpcid, avx512f, avx512dq, rdseed, adx, smap, avx512ifma, clflushopt, clwb, avx512cd, sha_ni, avx512bw, avx512vl, xsaveopt, xsavec, xgetbv1, xsaves, avx512_bf16, clzero, irperf, xsaveerptr, rdpru, wbnoinvd, arat, avx512vbmi, umip, pku, ospke, avx512_vbmi2, gfni, vaes, vpclmulqdq, avx512_vnni, avx512_bitalg, avx512_vpopcntdq, rdpid, fsrm
Ecpus
16
Scalability
50

System Resources and Accelerators

MEMORY
Memory Amount
128 GiB
Memory Amount Actual
128 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
      20 Gbps
      Inbound Traffic
      0 GB/month
      Outbound Traffic
      0 GB/month
      IPv4
      0

      CPU and System Topology

      Server Description

      A balanced general-purpose instance featuring dedicated AMD EPYC processors, top-tier single-core compute, and strong cryptographic performance for enterprise workloads.

      General Purpose

      Alibaba Cloud ecs.g8ae.8xlarge is a general-purpose instance featuring 32 dedicated x86_64 vCPUs powered by an AMD EPYC 9T34 processor running at 3.4 GHz. It is configured with 128.0 GB of system memory, yielding a balanced 4.0 GB per core, and operates on the KVM hypervisor with a 20 Gbps baseline network bandwidth. The instance lacks local storage and GPU accelerators. In benchmark evaluations, it delivers top-tier single-core CPU performance alongside strong cryptographic and memory capabilities, both ranking in the top 25%. Multi-core compute and memory bandwidth fall within average ranges. Given its dedicated resource allocation and balanced hardware profile, this instance is suitable for enterprise web serving, cryptographic tasks, and general-purpose workloads that do not require local storage.

      Economics

      Average Price per Region

      Prices per Zone

      Lowest Prices

      Performance

      Workload Profiles

      1.49Score
      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) 2,963,348 ops/sec 1,910,660 ops/sec 1.55 50.00% 50.00% +24.50%
      Redis RPS (pipeline=16, SET) 22,863,134 ops/sec 11,608,287 ops/sec 1.97 20.00% 20.00% +14.50%
      PassMark Memory Mark (composite) 2,913 2,416 1.21 10.00% 10.00% +1.92%
      Memory bandwidth (read, 16 MB ~ L3) 110,402 MB/sec 107,896 MB/sec 1.02 10.00% 10.00% +0.20%
      PassMark single-thread CPU 2,926 Mops/s 2,364 Mops/s 1.24 10.00% 10.00% +2.17%

      Memory Bandwidth

      Compression

      OpenSSL

      Passmark CPU Scores

      BENCHMARKSCORE
      Mark
      		 47478
      Compression
      		 626684
      Encryption
      		 38992
      Extended Instructions
      		 44518
      Floating Point Maths
      		 86161
      Integer Maths
      		 154073
      Physics
      		 5190
      Prime Numbers
      		 251
      Single Threaded
      		 2926
      String Sorting
      		 90917

      Passmark Memory Scores

      BENCHMARKSCORE
      Memory Mark
      		 2913
      Database Operations
      		 15890
      Memory Latency
      		 71
      Memory Read Cached
      		 27489
      Memory Read Uncached
      		 26568
      Memory Write
      		 26074

      Stress-ng Raw Scores

      Stress-ng Relative Multicore Performance

      Static Web Server

      Redis

      Alternatives

      Servers of the Same Family

      INSTANCEvCPUsMEMORYGPUs
      ecs.g8ae.large 28 GiB0
      ecs.g8ae.xlarge 416 GiB0
      ecs.g8ae.2xlarge 832 GiB0
      ecs.g8ae.4xlarge 1664 GiB0
      ecs.g8ae.16xlarge 64256 GiB0
      ecs.g8ae.32xlarge 128512 GiB0

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      ecs.g8ae.8xlarge FAQs