ecs.c7a.8xlarge by Alibaba Cloud

ecs.c7a.8xlarge is a ecs.c7a family (32 vCPUs, 64 GiB RAM, 0 GB storage) server offered by Alibaba Cloud with 32 vCPUs, 64 GiB of memory and 0 GB of storage. The pricing starts at 0.1379 USD per hour.
32 vCPU
64 GiB Memory
Spare SCore
43,132
(All-cores)
2,696
(Single-core)

Specifications

Server Metadata

Vendor ID
alicloud
Name
ecs.c7a.8xlarge
Description
ecs.c7a family (32 vCPUs, 64 GiB RAM, 0 GB storage)
Family
ecs.c7a
Hw Virt
Status
active
Observed At
2026-10-27T03:17:14.552122

Availability

REGION / IDSPOTONDEMAND
Ulanqab (CN) / cn-wulanchabu
0.1439 USD/h 0.654 USD/h
Chengdu (CN) / cn-chengdu
0.1379 USD/h 0.726 USD/h
Guangzhou (CN) / cn-guangzhou
0.1597 USD/h 0.726 USD/h
Beijing (CN) / cn-beijing
- 0.726 USD/h
Hangzhou (CN) / cn-hangzhou
- 0.726 USD/h
Shanghai (CN) / cn-shanghai
- 0.726 USD/h
Shenzhen (CN) / cn-shenzhen
- 0.726 USD/h
Frankfurt (DE) / eu-central-1
0.22515 USD/h 1.0982 USD/h
Virginia (US) / us-east-1
0.2087 USD/h 1.0986 USD/h
Hong Kong (HK) / cn-hongkong
0.3112 USD/h 1.1968 USD/h
Singapore (SG) / ap-southeast-1
- 1.1968 USD/h
Tokyo (JP) / ap-northeast-1
0.26765 USD/h 1.3056 USD/h

Processor

vCPUs
32
Hypervisor
KVM
CPU Allocation
Dedicated
CPU Cores
16
CPU Speed
2.55 GHz
CPU Architecture
x86_64
CPU Manufacturer
AMD
CPU Family
EPYC
CPU Model
7T83
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
512 KiB
CPU L2 Cache Total
8 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, 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, cr8_legacy, abm, sse4a, misalignsse, 3dnowprefetch, osvw, topoext, ssbd, ibrs, ibpb, stibp, vmmcall, tsc_adjust, bmi1, avx2, smep, bmi2, erms, invpcid, rdseed, adx, smap, clflushopt, clwb, sha_ni, xsaveopt, xsavec, xgetbv1, xsaves, clzero, xsaveerptr, wbnoinvd, arat, vaes, vpclmulqdq, rdpid, fsrm
Ecpus
16
Scalability
50

System Resources and Accelerators

MEMORY
Memory Amount
64 GiB
Memory Amount Actual
64 GiB
ACCELERATORS
Accelerator Count
0
Accelerator Memory Min
0 MiB
Accelerator Memory Total
0 MiB
Accelerators
    STORAGE
    Storage Size
    0 GB
    Storages
      NETWORK
      Network Speed Baseline
      8 Gbps
      Inbound Traffic
      0 GB/month
      Outbound Traffic
      0 GB/month
      IPv4
      0

      CPU and System Topology

      Server Description

      A 32-vCPU compute instance featuring AMD EPYC performance, strong single-core benchmarks, and high-speed text generation for lightweight inference workloads.

      Compute OptimizedGeneral Purpose

      Alibaba Cloud ecs.c7a.8xlarge is a compute-optimized instance driven by a 2.55 GHz AMD EPYC 7T83 processor featuring 16 physical cores and 32 dedicated vCPUs. Configured with 64 GB of memory, it delivers a focused 1:2 vCPU-to-RAM ratio alongside 8 Gbps baseline network bandwidth, operating without local storage or discrete GPUs. Single-core processing in stress-ng benchmarks and PassMark memory performance reach top-tier brackets, while small-model LLM text generation achieves 287.51 tokens per second. Multi-core operations, software compilation, and web serving benchmarks sit comfortably in average tiers. A notable tradeoff is lower uncached memory write throughput. Providing dedicated CPU resources without local disk overhead, this instance delivers strong qualitative value for CPU-bound tasks, code compilation, small AI inference, and backend web services.

      Economics

      Average Price per Region

      Prices per Zone

      Lowest Prices

      Performance

      Workload Profiles

      1.1Score
      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) 2,345,840 ops/sec 1,918,343 ops/sec 1.2 50.00% 50.00% +9.50%
      Redis RPS (pipeline=16, SET) 17,686,520 ops/sec 11,704,734 ops/sec 1.5 20.00% 20.00% +8.40%
      PassMark Memory Mark (composite) 2,772 2,416 1.2 10.00% 10.00% +1.80%
      Memory bandwidth (read, 16 MB ~ L3) 43,970 MB/sec 108,420 MB/sec 0.4 10.00% 10.00% -8.80%
      PassMark single-thread CPU 2,383 Mops/s 2,365 Mops/s 1 10.00% 10.00% 0.00%

      Memory Bandwidth

      Compression

      OpenSSL

      Geekbench Single-Core

      Score: 1,529

      Geekbench Multi-Core

      Score: 11,323

      Passmark CPU Scores

      BENCHMARKSCORE
      Mark
      		 35,963
      Compression
      		 501,636
      Encryption
      		 34,036
      Extended Instructions
      		 29,886
      Floating Point Maths
      		 72,671
      Integer Maths
      		 132,932
      Physics
      		 2,135
      Prime Numbers
      		 160
      Single Threaded
      		 2,383
      String Sorting
      		 57,557

      Passmark Memory Scores

      BENCHMARKSCORE
      Memory Mark
      		 2,772
      Database Operations
      		 10,909
      Memory Latency
      		 57
      Memory Read Cached
      		 23,662
      Memory Read Uncached
      		 17,497
      Memory Write
      		 15,445

      Stress-ng Stressors

      CPU integerSingleMultiScaling
      atomic
      		 207.53 165.69 0.80×
      bitops
      		 141,080 2,613,344 18.52×
      branch
      		 164,174 4,817,850 29.35×
      funccall
      		 540.2 11,240 20.81×
      funcret
      		 17,150 355,974 20.76×
      hash
      		 136,659 3,337,540 24.42×
      intmath
      		 58,227 1,260,382 21.65×
      nop
      		 282,986 4,563,790 16.13×
      prime
      		 392,008 7,739,495 19.74×
      rotate
      		 77,137 1,236,930 16.04×
      str
      		 867,381 16,930,833 19.52×
      wcs
      		 560,697 10,545,619 18.81×
      CryptographySingleMultiScaling
      crypt
      		 3,206 51,633 16.11×
      CompressionSingleMultiScaling
      jpeg
      		 686.84 15,046 21.91×
      zlib
      		 46.47 1,472 31.68×
      HypervisorSingleMultiScaling
      clock
      		 22,175 258,963 11.68×
      clone
      		 290.59 4,029 13.86×
      context
      		 3,146 84,060 26.72×
      cpu-sched
      		 62.72 2,054 32.74×
      eventfd
      		 63,731 1,241,671 19.48×
      fault
      		 7,904 175,933 22.26×
      fork
      		 3,512 61,256 17.44×
      getrandom
      		 45,262 918,106 20.28×
      hrtimers
      		 142,793 3,498,326 24.50×
      mprotect
      		 771,764 5,136,286 6.66×
      mtx
      		 49,277,602 1,555,554,477 31.57×
      munmap
      		 2,456 45,065 18.35×
      null
      		 409,017 10,453,168 25.56×
      pipe
      		 1,466,561 10,378,157 7.08×
      priv-instr
      		 410,542 10,088,356 24.57×
      resched
      		 6,801,702 2,847,376 0.42×
      switch
      		 133,972 3,095,096 23.10×
      timermix
      		 253,716 5,989,342 23.61×
      tlb-shootdown
      		 13,740 95,278 6.93×
      tsc
      		 668,280 20,571,110 30.78×
      usersyscall
      		 295,273 7,337,036 24.85×
      vdso
      		 77,206,490 2,091,771,174 27.09×
      vfork
      		 21,173 137,745 6.51×
      x86syscall
      		 4,865,712 124,223,100 25.53×
      yield
      		 20,922,563 19,428,665 0.93×
      zero
      		 2,786,924 66,810,010 23.97×
      CPU float/SIMDSingleMultiScaling
      eigen
      		 13,996 230,730 16.49×
      expmath
      		 2,392 61,404 25.67×
      fma
      		 778,469 19,735,613 25.35×
      fp
      		 226.96 5,281 23.27×
      fractal
      		 6.8 178.49 26.25×
      hyperbolic
      		 3,288 79,965 24.32×
      logmath
      		 3,868 89,048 23.02×
      matrix
      		 2,715 64,415 23.73×
      matrix-3d
      		 259.62 1,480 5.70×
      monte-carlo
      		 182.6 4,479 24.53×
      mpfr
      		 1,398 27,324 19.55×
      powmath
      		 1,129 31,271 27.70×
      trig
      		 1,489 36,886 24.77×
      veccmp
      		 15,980 337,083 21.09×
      vecfp
      		 1,477 32,968 22.31×
      vecmath
      		 3,412 88,327 25.88×
      vecshuf
      		 532.46 9,951 18.69×
      vecwide
      		 23,647 482,352 20.40×
      AlgorithmsSingleMultiScaling
      bitonicsort
      		 8.6 147.2 17.12×
      bsearch
      		 260.71 5,531 21.21×
      bubblesort
      		 0.8 19.2 24.00×
      fibsearch
      		 320.42 6,175 19.27×
      heapsort
      		 9.39 184.8 19.68×
      hsearch
      		 7,550 138,934 18.40×
      insertionsort
      		 11.6 185.6 16.00×
      malloc
      		 3,178,739 54,932,112 17.28×
      mcontend
      		 132.88 5,602 42.16×
      mergesort
      		 27.6 639.78 23.18×
      qsort
      		 18.8 403.19 21.45×
      skiplist
      		 6,150 151,799 24.68×
      tree
      		 1.6 19.18 11.99×
      MemorySingleMultiScaling
      cache
      		 650,709 1,061,762 1.63×
      cachehammer
      		 307,702 6,004,897 19.52×
      cacheline
      		 28.78 1,326 46.06×
      l1cache
      		 158.36 2,525 15.94×
      memcpy
      		 365.84 5,596 15.30×
      memrate
      		 2.54 5.94 2.34×
      memthrash
      		 138.83 386.72 2.79×
      ptr-chase
      		 39,261,974 207,184,225 5.28×
      spinmem
      		 358.18 2,344 6.54×
      stream
      		 98.75 5,058 51.22×
      vm
      		 58,994 295,429 5.01×

      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

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