ecs.hfc6.8xlarge by Alibaba Cloud

ecs.hfc6.8xlarge is a ecs.hfc6 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 0.1601 USD per hour.
32 vCPU
64 GiB Memory
Spare SCore
30,632
(All-cores)
1,435
(Single-core)

Specifications

Server Metadata

Vendor ID
alicloud
Name
ecs.hfc6.8xlarge
Description
ecs.hfc6 family (32 vCPUs, 64 GiB RAM, 0 GB storage)
Family
ecs.hfc6
Hw Virt
Status
active
Observed At
2026-10-24T21:56:31.988277

Availability

REGION / IDSPOTONDEMAND
Ulanqab (CN) / cn-wulanchabu
- 0.9983 USD/h
Chengdu (CN) / cn-chengdu
0.1601 USD/h 1.0009 USD/h
Heyuan (CN) / cn-heyuan
0.2107 USD/h 1.109 USD/h
Beijing (CN) / cn-beijing
0.1775 USD/h 1.1092 USD/h
Guangzhou (CN) / cn-guangzhou
0.1775 USD/h 1.1092 USD/h
Shenzhen (CN) / cn-shenzhen
0.1775 USD/h 1.1092 USD/h
Hangzhou (CN) / cn-hangzhou
- 1.1092 USD/h
Shanghai (CN) / cn-shanghai
- 1.1092 USD/h
Virginia (US) / us-east-1
0.2645 USD/h 1.392 USD/h
Frankfurt (DE) / eu-central-1
- 1.584 USD/h
Jakarta (ID) / ap-southeast-5
0.304 USD/h 1.6 USD/h
London (GB) / eu-west-1
0.28015 USD/h 1.648 USD/h
Tokyo (JP) / ap-northeast-1
0.264 USD/h 1.76 USD/h
Hong Kong (HK) / cn-hongkong
0.37295 USD/h 1.776 USD/h
Riyadh (SA) / me-central-1
- 1.92 USD/h

Processor

vCPUs
32
Hypervisor
KVM
CPU Allocation
Dedicated
CPU Cores
16
CPU Speed
3.1 GHz
CPU Architecture
x86_64
CPU Manufacturer
Intel
CPU Family
Xeon
CPU Model
8269CY
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
36 MiB
CPU L3 Cache Total
36 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, 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, abm, 3dnowprefetch, pti, fsgsbase, tsc_adjust, bmi1, avx2, smep, bmi2, erms, invpcid, avx512f, avx512dq, rdseed, adx, smap, clflushopt, clwb, avx512cd, avx512bw, avx512vl, xsaveopt, xsavec, xgetbv1, xsaves, ida, arat, avx512_vnni
Ecpus
21.3
Scalability
66.56

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
      10 Gbps
      Inbound Traffic
      0 GB/month
      Outbound Traffic
      0 GB/month
      IPv4
      0

      CPU and System Topology

      Server Description

      A dedicated compute-optimized instance featuring high-frequency Intel Xeon processors and a balanced memory-to-CPU ratio for high-throughput workloads.

      Compute OptimizedGeneral Purpose

      Alibaba Cloud ecs.hfc6.8xlarge is a compute-optimized instance featuring 32 dedicated vCPUs and 64.0 GB of RAM, powered by an Intel Xeon 8269CY processor running at 3.1 GHz. Built on the x86_64 architecture and managed via the KVM hypervisor, this server provides a 1:2 vCPU-to-RAM ratio without local storage or GPU hardware. It delivers a baseline network bandwidth of 10 Gbps. Benchmark results indicate solid mid-range performance, with a multi-core Geekbench score of 10887.0 and a static web serving throughput of 20.59 GB/sec. The inclusion of AVX-512 instructions supports vector calculations, making it highly efficient for compute-bound workloads. This instance is well-suited for software compilation, web serving, and multi-threaded data decompression tasks where high CPU performance is required without the overhead of excess memory.

      Economics

      Average Price per Region

      Prices per Zone

      Lowest Prices

      Performance

      Workload Profiles

      1.4Score
      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) 3,113,092 ops/sec 1,919,289 ops/sec 1.6 50.00% 50.00% +26.00%
      Redis RPS (pipeline=16, SET) 17,691,620 ops/sec 11,728,058 ops/sec 1.5 20.00% 20.00% +8.40%
      PassMark Memory Mark (composite) 2,634 2,416 1.1 10.00% 10.00% +0.96%
      Memory bandwidth (read, 16 MB ~ L3) 112,297 MB/sec 108,466 MB/sec 1 10.00% 10.00% 0.00%
      PassMark single-thread CPU 2,154 Mops/s 2,365 Mops/s 0.92 10.00% 10.00% -0.83%

      Memory Bandwidth

      Compression

      OpenSSL

      Geekbench Single-Core

      Score: 1,279

      Geekbench Multi-Core

      Score: 10,887

      Passmark CPU Scores

      BENCHMARKSCORE
      Mark
      		 29,138
      Compression
      		 468,169
      Encryption
      		 14,153
      Extended Instructions
      		 28,628
      Floating Point Maths
      		 54,927
      Integer Maths
      		 102,356
      Physics
      		 2,075
      Prime Numbers
      		 131
      Single Threaded
      		 2,154
      String Sorting
      		 60,894

      Passmark Memory Scores

      BENCHMARKSCORE
      Memory Mark
      		 2,634
      Database Operations
      		 11,255
      Memory Latency
      		 52
      Memory Read Cached
      		 24,569
      Memory Read Uncached
      		 10,403
      Memory Write
      		 9,997

      Stress-ng Stressors

      CPU integerSingleMultiScaling
      atomic
      		 239.52 215.38 0.90×
      bitops
      		 125,870 2,246,026 17.84×
      branch
      		 158,372 3,846,755 24.29×
      funccall
      		 580.8 9,781 16.84×
      funcret
      		 11,801 275,279 23.33×
      hash
      		 134,394 3,178,693 23.65×
      intmath
      		 22,944 565,563 24.65×
      nop
      		 196,485 2,727,540 13.88×
      prime
      		 331,228 5,930,506 17.90×
      rotate
      		 99,347 2,005,582 20.19×
      str
      		 811,704 16,551,241 20.39×
      wcs
      		 520,985 9,595,106 18.42×
      CryptographySingleMultiScaling
      crypt
      		 2,505 39,184 15.64×
      CompressionSingleMultiScaling
      jpeg
      		 610.51 11,720 19.20×
      zlib
      		 61.07 1,331 21.80×
      HypervisorSingleMultiScaling
      clock
      		 16,502 275,139 16.67×
      clone
      		 443.86 5,998 13.51×
      context
      		 1,966 41,358 21.03×
      cpu-sched
      		 66.38 1,980 29.83×
      eventfd
      		 90,659 989,952 10.92×
      fault
      		 13,881 210,042 15.13×
      fork
      		 4,021 68,817 17.11×
      getrandom
      		 46,236 918,019 19.85×
      hrtimers
      		 441,866 2,732,679 6.18×
      mprotect
      		 1,099,767 4,928,521 4.48×
      mtx
      		 13,984,840 972,525,454 69.54×
      munmap
      		 2,927 50,834 17.37×
      null
      		 208,846 4,117,682 19.72×
      pipe
      		 853,548 7,711,338 9.03×
      priv-instr
      		 443,336 9,125,898 20.58×
      resched
      		 5,115,721 3,046,785 0.60×
      switch
      		 195,294 4,264,469 21.84×
      timermix
      		 315,932 8,189,725 25.92×
      tlb-shootdown
      		 11,076 58,746 5.30×
      tsc
      		 1,022,935 23,044,588 22.53×
      usersyscall
      		 308,821 6,340,043 20.53×
      vdso
      		 83,316,240 2,329,315,963 27.96×
      vfork
      		 30,666 152,846 4.98×
      x86syscall
      		 2,389,297 45,988,129 19.25×
      yield
      		 16,432,325 18,377,874 1.12×
      zero
      		 1,595,420 30,056,131 18.84×
      CPU float/SIMDSingleMultiScaling
      eigen
      		 16,735 305,445 18.25×
      expmath
      		 2,754 67,922 24.67×
      fma
      		 604,550 15,870,648 26.25×
      fp
      		 133.42 3,037 22.76×
      fractal
      		 5 119.22 23.84×
      hyperbolic
      		 2,852 72,348 25.36×
      logmath
      		 4,688 113,435 24.20×
      matrix
      		 3,183 80,059 25.16×
      matrix-3d
      		 651.8 2,982 4.57×
      monte-carlo
      		 107.39 2,368 22.05×
      mpfr
      		 1,255 21,746 17.33×
      powmath
      		 1,630 39,989 24.54×
      trig
      		 1,764 38,283 21.71×
      veccmp
      		 16,091 263,542 16.38×
      vecfp
      		 1,370 27,164 19.83×
      vecmath
      		 2,242 56,874 25.36×
      vecshuf
      		 579.14 9,986 17.24×
      vecwide
      		 24,822 454,232 18.30×
      AlgorithmsSingleMultiScaling
      bitonicsort
      		 7.4 139.2 18.81×
      bsearch
      		 255.9 4,730 18.48×
      bubblesort
      		 0.8 12.8 16.00×
      fibsearch
      		 288.42 5,904 20.47×
      heapsort
      		 8.6 172.6 20.07×
      hsearch
      		 5,284 101,495 19.21×
      insertionsort
      		 8.4 134.4 16.00×
      malloc
      		 2,296,062 33,261,096 14.49×
      mcontend
      		 116.07 8,752 75.40×
      mergesort
      		 27.4 560.58 20.46×
      qsort
      		 19.4 383.59 19.77×
      skiplist
      		 5,389 121,691 22.58×
      tree
      		 1.6 19.18 11.99×
      MemorySingleMultiScaling
      cache
      		 389,951 617,350 1.58×
      cachehammer
      		 380,089 9,551,317 25.13×
      cacheline
      		 33.96 2,517 74.11×
      l1cache
      		 233.01 4,017 17.24×
      memcpy
      		 392.47 6,344 16.16×
      memrate
      		 1.37 11.91 8.69×
      memthrash
      		 257.26 682.97 2.65×
      ptr-chase
      		 33,840,634 280,443,984 8.29×
      spinmem
      		 399.79 2,351 5.88×
      stream
      		 33.49 7,323 218.67×
      vm
      		 57,422 297,176 5.18×

      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

      INSTANCEvCPUsMEMORYAccelerators
      ecs.hfc6.large 24 GiB0
      ecs.hfc6.xlarge 48 GiB0
      ecs.hfc6.2xlarge 816 GiB0
      ecs.hfc6.3xlarge 1224 GiB0
      ecs.hfc6.4xlarge 1632 GiB0
      ecs.hfc6.6xlarge 2448 GiB0
      ecs.hfc6.10xlarge 4096 GiB0

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      ecs.hfc6.8xlarge FAQs