ecs.hfg6.4xlarge by Alibaba Cloud

ecs.hfg6.4xlarge is a ecs.hfg6 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 0.0979 USD per hour.
16 vCPU
64 GiB Memory
Spare SCore
15,351
(All-cores)
1,439
(Single-core)

Specifications

Server Metadata

Vendor ID
alicloud
Name
ecs.hfg6.4xlarge
Description
ecs.hfg6 family (16 vCPUs, 64 GiB RAM, 0 GB storage)
Family
ecs.hfg6
Hw Virt
Status
active
Observed At
2026-10-23T21:32:38.421873

Availability

REGION / IDSPOTONDEMAND
Ulanqab (CN) / cn-wulanchabu
0.1165 USD/h 0.6129 USD/h
Chengdu (CN) / cn-chengdu
0.1166 USD/h 0.6139 USD/h
Guangzhou (CN) / cn-guangzhou
0.1294 USD/h 0.681 USD/h
Heyuan (CN) / cn-heyuan
0.1294 USD/h 0.681 USD/h
Beijing (CN) / cn-beijing
- 0.681 USD/h
Hangzhou (CN) / cn-hangzhou
- 0.681 USD/h
Shanghai (CN) / cn-shanghai
- 0.681 USD/h
Shenzhen (CN) / cn-shenzhen
- 0.681 USD/h
Virginia (US) / us-east-1
0.0979 USD/h 0.816 USD/h
Silicon Valley (US) / us-west-1
0.0979 USD/h 0.816 USD/h
London (GB) / eu-west-1
0.1652 USD/h 0.944 USD/h
Frankfurt (DE) / eu-central-1
0.187 USD/h 0.984 USD/h
Jakarta (ID) / ap-southeast-5
0.1946 USD/h 1.024 USD/h
Singapore (SG) / ap-southeast-1
- 1.024 USD/h
Tokyo (JP) / ap-northeast-1
0.169 USD/h 1.056 USD/h
Hong Kong (HK) / cn-hongkong
- 1.128 USD/h
Riyadh (SA) / me-central-1
- 1.2288 USD/h

Processor

vCPUs
16
Hypervisor
KVM
CPU Allocation
Dedicated
CPU Cores
8
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
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
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
10.7
Scalability
66.88

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

      CPU and System Topology

      Server Description

      A dedicated x86_64 compute instance with a balanced memory-to-vCPU ratio, designed for predictable general-purpose workloads and web serving.

      General PurposeCompute Optimized

      Alibaba Cloud ecs.hfg6.4xlarge is an x86_64 server instance featuring a dedicated Intel Xeon 8269CY processor with 16 vCPUs, 8 physical cores, and a 3.1 GHz clock speed. It is equipped with 64.0 GB of RAM, providing a balanced 1:4 vCPU-to-memory ratio, but includes no local storage or GPU resources. Network bandwidth is rated at a baseline of 5 Gbps. Performance benchmarks place the instance in the average tier, with a Geekbench multi-core score of 7869.0 and a static web serving throughput of 12.4 GB/sec. While it handles lightweight LLM inference and Redis operations efficiently, prompt processing performance drops significantly on larger 7B models. This instance is suited for general-purpose applications, database operations, and web serving where dedicated CPU resources are required without local storage.

      Economics

      Average Price per Region

      Prices per Zone

      Lowest Prices

      Performance

      Workload Profiles

      0.86Score
      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) 1,591,539 ops/sec 1,919,289 ops/sec 0.84 50.00% 50.00% -8.30%
      Redis RPS (pipeline=16, SET) 9,501,203 ops/sec 11,728,058 ops/sec 0.79 20.00% 20.00% -4.60%
      PassMark Memory Mark (composite) 2,580 2,416 1.1 10.00% 10.00% +0.96%
      Memory bandwidth (read, 16 MB ~ L3) 94,981 MB/sec 108,466 MB/sec 0.86 10.00% 10.00% -1.50%
      PassMark single-thread CPU 2,157 Mops/s 2,365 Mops/s 0.92 10.00% 10.00% -0.83%

      Memory Bandwidth

      Compression

      OpenSSL

      Geekbench Single-Core

      Score: 1,284

      Geekbench Multi-Core

      Score: 7,869

      Passmark CPU Scores

      BENCHMARKSCORE
      Mark
      		 16,806
      Compression
      		 236,427
      Encryption
      		 7,104
      Extended Instructions
      		 14,388
      Floating Point Maths
      		 27,531
      Integer Maths
      		 51,333
      Physics
      		 1,659
      Prime Numbers
      		 95
      Single Threaded
      		 2,157
      String Sorting
      		 31,099

      Passmark Memory Scores

      BENCHMARKSCORE
      Memory Mark
      		 2,580
      Database Operations
      		 5,932
      Memory Latency
      		 52
      Memory Read Cached
      		 24,762
      Memory Read Uncached
      		 10,281
      Memory Write
      		 10,021

      Stress-ng Stressors

      CPU integerSingleMultiScaling
      atomic
      		 249.77 235.13 0.94×
      bitops
      		 126,310 1,125,947 8.91×
      branch
      		 158,859 1,929,255 12.14×
      funccall
      		 584.63 4,918 8.41×
      funcret
      		 11,771 138,322 11.75×
      hash
      		 134,705 1,592,237 11.82×
      intmath
      		 23,233 283,904 12.22×
      nop
      		 197,113 1,366,367 6.93×
      prime
      		 333,582 2,973,002 8.91×
      rotate
      		 99,629 1,004,768 10.09×
      str
      		 855,668 8,756,637 10.23×
      wcs
      		 538,950 4,693,803 8.71×
      CryptographySingleMultiScaling
      crypt
      		 2,486 19,628 7.90×
      CompressionSingleMultiScaling
      jpeg
      		 638.38 6,183 9.69×
      zlib
      		 48.64 672.83 13.83×
      HypervisorSingleMultiScaling
      clock
      		 17,745 183,162 10.32×
      clone
      		 435.95 3,556 8.16×
      context
      		 1,949 21,016 10.78×
      cpu-sched
      		 58.89 1,041 17.68×
      eventfd
      		 90,107 916,862 10.18×
      fault
      		 14,018 139,214 9.93×
      fork
      		 4,284 40,093 9.36×
      getrandom
      		 46,339 460,457 9.94×
      hrtimers
      		 171,703 1,791,437 10.43×
      mprotect
      		 1,056,506 2,503,501 2.37×
      mtx
      		 9,431,816 479,811,076 50.87×
      munmap
      		 3,008 30,528 10.15×
      null
      		 212,572 2,103,960 9.90×
      pipe
      		 934,125 4,887,677 5.23×
      priv-instr
      		 446,737 4,652,742 10.41×
      resched
      		 3,448,551 1,532,111 0.44×
      switch
      		 180,756 2,099,601 11.62×
      timermix
      		 351,520 4,844,411 13.78×
      tlb-shootdown
      		 13,321 36,575 2.75×
      tsc
      		 1,026,547 11,547,369 11.25×
      usersyscall
      		 314,355 3,234,209 10.29×
      vdso
      		 83,547,067 1,184,440,660 14.18×
      vfork
      		 32,041 194,233 6.06×
      x86syscall
      		 2,381,647 23,477,233 9.86×
      yield
      		 8,763,919 8,936,894 1.02×
      zero
      		 1,622,659 15,166,485 9.35×
      CPU float/SIMDSingleMultiScaling
      eigen
      		 16,804 163,339 9.72×
      expmath
      		 2,763 33,965 12.29×
      fma
      		 605,876 7,960,357 13.14×
      fp
      		 130.82 1,508 11.52×
      fractal
      		 5 59.8 11.96×
      hyperbolic
      		 2,866 36,181 12.63×
      logmath
      		 4,701 56,833 12.09×
      matrix
      		 3,115 40,375 12.96×
      matrix-3d
      		 668.52 3,000 4.49×
      monte-carlo
      		 107.41 1,188 11.06×
      mpfr
      		 1,254 10,920 8.71×
      powmath
      		 1,636 20,056 12.26×
      trig
      		 1,770 19,213 10.86×
      veccmp
      		 16,088 132,325 8.23×
      vecfp
      		 1,374 13,632 9.92×
      vecmath
      		 2,251 28,495 12.66×
      vecshuf
      		 581.29 5,004 8.61×
      vecwide
      		 25,090 227,692 9.07×
      AlgorithmsSingleMultiScaling
      bitonicsort
      		 7.4 70 9.46×
      bsearch
      		 252.04 2,362 9.37×
      bubblesort
      		 0.8 6.4 8.00×
      fibsearch
      		 289.42 2,966 10.25×
      heapsort
      		 8.6 86.4 10.05×
      hsearch
      		 5,282 51,033 9.66×
      insertionsort
      		 8.4 67.2 8.00×
      malloc
      		 2,325,345 27,761,445 11.94×
      mcontend
      		 131.3 4,479 34.11×
      mergesort
      		 27.6 287.79 10.43×
      qsort
      		 19.4 191.8 9.89×
      skiplist
      		 5,404 60,971 11.28×
      tree
      		 1.4 12.79 9.14×
      MemorySingleMultiScaling
      cache
      		 392,153 783,907 2.00×
      cachehammer
      		 380,748 5,326,572 13.99×
      cacheline
      		 36.53 632.77 17.32×
      l1cache
      		 234.44 2,020 8.61×
      memcpy
      		 393.64 3,185 8.09×
      memrate
      		 1.37 9.12 6.66×
      memthrash
      		 197.04 575.51 2.92×
      ptr-chase
      		 36,195,256 169,530,442 4.68×
      spinmem
      		 390.59 1,167 2.99×
      stream
      		 33.5 4,108 122.63×
      vm
      		 58,224 293,701 5.04×

      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.hfg6.large 28 GiB0
      ecs.hfg6.xlarge 416 GiB0
      ecs.hfg6.2xlarge 832 GiB0
      ecs.hfg6.3xlarge 1248 GiB0
      ecs.hfg6.6xlarge 2496 GiB0
      ecs.hfg6.8xlarge 32128 GiB0
      ecs.hfg6.10xlarge 40192 GiB0

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      ecs.hfg6.4xlarge FAQs