ecs.c7a.16xlarge by Alibaba Cloud

ecs.c7a.16xlarge is a ecs.c7a family (64 vCPUs, 128 GiB RAM, 0 GB storage) server offered by Alibaba Cloud with 64 vCPUs, 128 GiB of memory and 0 GB of storage. The pricing starts at 0.2761 USD per hour.
64 vCPU
128 GiB Memory
Spare SCore
86,350
(All-cores)
2,697
(Single-core)

Specifications

Server Metadata

Vendor ID
alicloud
Name
ecs.c7a.16xlarge
Description
ecs.c7a family (64 vCPUs, 128 GiB RAM, 0 GB storage)
Family
ecs.c7a
Hw Virt
Status
active
Observed At
2026-10-16T13:33:29.228123

Availability

REGION / IDSPOTONDEMAND
Ulanqab (CN) / cn-wulanchabu
- 1.308 USD/h
Beijing (CN) / cn-beijing
0.2979 USD/h 1.453 USD/h
Chengdu (CN) / cn-chengdu
0.2761 USD/h 1.453 USD/h
Guangzhou (CN) / cn-guangzhou
- 1.453 USD/h
Hangzhou (CN) / cn-hangzhou
- 1.453 USD/h
Shanghai (CN) / cn-shanghai
- 1.453 USD/h
Shenzhen (CN) / cn-shenzhen
- 1.453 USD/h
Frankfurt (DE) / eu-central-1
- 2.1964 USD/h
Virginia (US) / us-east-1
0.4175 USD/h 2.1972 USD/h
Singapore (SG) / ap-southeast-1
- 2.3936 USD/h
Tokyo (JP) / ap-northeast-1
0.5353 USD/h 2.6112 USD/h

Processor

vCPUs
64
Hypervisor
KVM
CPU Allocation
Dedicated
CPU Cores
32
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
1 MiB
CPU L1I Cache
32 KiB
CPU L1I Cache Total
1 MiB
CPU L2 Cache
512 KiB
CPU L2 Cache Total
16 MiB
CPU L3 Cache
32 MiB
CPU L3 Cache Total
128 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
32
Scalability
50

System Resources and Accelerators

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

      Server Description

      A high-density compute-optimized server with 64 dedicated virtual cores designed for intensive parallel processing, software compilation, and in-memory caching.

      Compute Optimized

      Alibaba Cloud ecs.c7a.16xlarge is a compute-optimized cloud instance powered by an AMD EPYC 7T83 processor running at 2.55 GHz across 32 physical cores and 64 dedicated vCPUs. Configured with 128 GB of RAM (2.0 GB per core) and a 16 Gbps baseline network interface, this instance omits local disk storage and GPU hardware, relying on network-attached block storage for persistent data. Benchmark results highlight top-tier multi-core execution in stress-ng and PassMark CPU evaluations, alongside strong performance in cryptography, image processing, and Redis key-value operations reaching 61.81 million SET operations per second. While uncached memory throughput and single-threaded gzip compression rank in the average tier, the 1:2 vCPU-to-RAM balance maximizes compute resource density. This profile provides high cost efficiency for CPU-bound microservices, software compilation, CI/CD pipelines, parallelized data processing, and in-memory caching workloads.

      Economics

      Average Price per Region

      Prices per Zone

      Lowest Prices

      Performance

      Workload Profiles

      1.9Score
      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) 4,671,900 ops/sec 1,919,289 ops/sec 2.5 50.00% 50.00% +58.00%
      Redis RPS (pipeline=16, SET) 35,309,546 ops/sec 11,728,058 ops/sec 2.9 20.00% 20.00% +24.00%
      PassMark Memory Mark (composite) 2,971 2,416 1.2 10.00% 10.00% +1.80%
      Memory bandwidth (read, 16 MB ~ L3) 87,600 MB/sec 108,466 MB/sec 0.8 10.00% 10.00% -2.20%
      PassMark single-thread CPU 2,388 Mops/s 2,365 Mops/s 1 10.00% 10.00% 0.00%

      Memory Bandwidth

      Compression

      OpenSSL

      Geekbench Single-Core

      Score: 1,532

      Geekbench Multi-Core

      Score: 14,302

      Passmark CPU Scores

      BENCHMARKSCORE
      Mark
      		 59,200
      Compression
      		 1,000,668
      Encryption
      		 68,061
      Extended Instructions
      		 55,825
      Floating Point Maths
      		 145,362
      Integer Maths
      		 265,946
      Physics
      		 4,266
      Prime Numbers
      		 320
      Single Threaded
      		 2,388
      String Sorting
      		 114,320

      Passmark Memory Scores

      BENCHMARKSCORE
      Memory Mark
      		 2,971
      Database Operations
      		 22,043
      Memory Latency
      		 55
      Memory Read Cached
      		 23,679
      Memory Read Uncached
      		 18,173
      Memory Write
      		 15,858

      Stress-ng Stressors

      CPU integerSingleMultiScaling
      atomic
      		 481.8 150.47 0.31×
      bitops
      		 141,280 5,230,535 37.02×
      branch
      		 164,268 9,683,673 58.95×
      funccall
      		 540.49 22,364 41.38×
      funcret
      		 17,145 713,396 41.61×
      hash
      		 136,670 6,665,537 48.77×
      intmath
      		 58,288 2,524,335 43.31×
      nop
      		 282,860 9,127,662 32.27×
      prime
      		 390,943 15,513,599 39.68×
      rotate
      		 77,079 2,472,313 32.08×
      str
      		 857,031 32,813,368 38.29×
      wcs
      		 563,073 20,252,805 35.97×
      CryptographySingleMultiScaling
      crypt
      		 3,220 102,808 31.93×
      CompressionSingleMultiScaling
      jpeg
      		 689.54 29,958 43.45×
      zlib
      		 51.38 2,824 54.96×
      HypervisorSingleMultiScaling
      clock
      		 20,277 238,057 11.74×
      clone
      		 265.2 5,987 22.57×
      context
      		 3,155 168,192 53.31×
      cpu-sched
      		 56.44 4,080 72.29×
      eventfd
      		 64,743 3,098,483 47.86×
      fault
      		 7,848 134,036 17.08×
      fork
      		 3,328 67,006 20.13×
      getrandom
      		 45,225 1,837,440 40.63×
      hrtimers
      		 156,429 5,391,187 34.46×
      mprotect
      		 605,298 10,005,979 16.53×
      mtx
      		 43,742,054 3,109,822,264 71.09×
      munmap
      		 2,371 67,583 28.50×
      null
      		 407,531 20,920,009 51.33×
      pipe
      		 1,498,365 19,707,744 13.15×
      priv-instr
      		 410,699 18,368,498 44.72×
      resched
      		 7,547,066 5,863,601 0.78×
      switch
      		 135,255 6,460,456 47.77×
      timermix
      		 252,511 11,852,225 46.94×
      tlb-shootdown
      		 12,498 155,332 12.43×
      tsc
      		 665,382 41,190,551 61.91×
      usersyscall
      		 298,550 14,289,799 47.86×
      vdso
      		 76,999,823 4,189,217,457 54.41×
      vfork
      		 20,226 96,361 4.76×
      x86syscall
      		 4,859,231 248,941,310 51.23×
      yield
      		 35,920,097 38,125,054 1.06×
      zero
      		 2,792,121 133,818,323 47.93×
      CPU float/SIMDSingleMultiScaling
      eigen
      		 14,071 461,731 32.81×
      expmath
      		 2,437 125,304 51.42×
      fma
      		 779,027 39,491,020 50.69×
      fp
      		 227.63 10,505 46.15×
      fractal
      		 6.8 357.21 52.53×
      hyperbolic
      		 3,287 160,600 48.86×
      logmath
      		 3,872 178,575 46.12×
      matrix
      		 2,712 127,755 47.11×
      matrix-3d
      		 818.37 2,966 3.62×
      monte-carlo
      		 182.62 8,960 49.06×
      mpfr
      		 1,397 54,566 39.05×
      powmath
      		 1,203 62,245 51.75×
      trig
      		 1,490 73,856 49.58×
      veccmp
      		 15,972 674,871 42.25×
      vecfp
      		 1,479 65,068 44.01×
      vecmath
      		 3,413 176,822 51.81×
      vecshuf
      		 533.74 19,921 37.32×
      vecwide
      		 23,657 964,747 40.78×
      AlgorithmsSingleMultiScaling
      bitonicsort
      		 8.8 294.39 33.45×
      bsearch
      		 259.86 11,151 42.91×
      bubblesort
      		 0.8 38.4 48.00×
      fibsearch
      		 320.33 12,291 38.37×
      heapsort
      		 9.2 361 39.24×
      hsearch
      		 7,267 278,622 38.34×
      insertionsort
      		 11.6 359.2 30.97×
      malloc
      		 3,105,999 83,942,178 27.03×
      mcontend
      		 106.07 9,962 93.92×
      mergesort
      		 28.2 1,295 45.91×
      qsort
      		 18.6 799.18 42.97×
      skiplist
      		 6,207 302,710 48.77×
      tree
      		 1.6 38.37 23.98×
      MemorySingleMultiScaling
      cache
      		 481,167 1,155,049 2.40×
      cachehammer
      		 297,293 9,898,192 33.29×
      cacheline
      		 31.37 2,149 68.51×
      l1cache
      		 151.41 4,767 31.49×
      memcpy
      		 365.83 11,161 30.51×
      memrate
      		 2.55 12.03 4.72×
      memthrash
      		 190.71 738.65 3.87×
      ptr-chase
      		 39,541,099 414,777,888 10.49×
      spinmem
      		 360.17 4,649 12.91×
      stream
      		 49.73 9,966 200.41×
      vm
      		 58,953 300,660 5.10×

      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

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