ecs.gn5-c8g1.4xlarge by Alibaba Cloud

ecs.gn5-c8g1.4xlarge is a ecs.gn5 family (16 vCPUs, 120 GiB RAM, 944 GB ssd storage, 2xP100 16384 GiB VRAM) server offered by Alibaba Cloud with 16 vCPUs, 120 GiB of memory and 944 GB of storage. The pricing starts at 0.3071 USD per hour.
16 vCPU
120 GiB Memory
944 GB Storage
2 GPU
Spare SCore
9,532
(All-cores)
954
(Single-core)

Specifications

Server Metadata

Vendor ID
alicloud
Name
ecs.gn5-c8g1.4xlarge
Description
ecs.gn5 family (16 vCPUs, 120 GiB RAM, 944 GB ssd storage, 2xP100 16384 GiB VRAM)
Family
ecs.gn5
Hw Virt
Average Time To Start
17
Status
active
Observed At
2026-10-24T11:32:00.640433

Availability

REGION / IDSPOTONDEMAND
Virginia (US) / us-east-1
0.3362 USD/h 3.735 USD/h
Frankfurt (DE) / eu-central-1
- 3.884 USD/h
Silicon Valley (US) / us-west-1
0.3697 USD/h 4.108 USD/h
Zhangjiakou (CN) / cn-zhangjiakou
0.3488 USD/h 4.36 USD/h
Tokyo (JP) / ap-northeast-1
0.3071 USD/h 4.387 USD/h
Beijing (CN) / cn-beijing
0.3388 USD/h 4.84 USD/h
Ulanqab (CN) / cn-wulanchabu
0.3388 USD/h 4.84 USD/h
Hangzhou (CN) / cn-hangzhou
- 4.84 USD/h
Shanghai (CN) / cn-shanghai
- 4.84 USD/h
Shenzhen (CN) / cn-shenzhen
- 4.84 USD/h

Processor

vCPUs
16
Hypervisor
KVM
CPU Allocation
Dedicated
CPU Cores
8
CPU Speed
2.5 GHz
CPU Architecture
x86_64
CPU Manufacturer
Intel
CPU Family
Xeon
CPU Model
E5-2682 v4
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
256 KiB
CPU L2 Cache Total
2 MiB
CPU L3 Cache
40 MiB
CPU L3 Cache Total
40 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, tsc_known_freq, pni, pclmulqdq, ssse3, fma, cx16, pcid, sse4_1, sse4_2, x2apic, movbe, popcnt, tsc_deadline_timer, aes, xsave, avx, f16c, rdrand, hypervisor, lahf_lm, abm, 3dnowprefetch, pti, ibrs, ibpb, stibp, fsgsbase, tsc_adjust, bmi1, hle, avx2, smep, bmi2, erms, invpcid, rtm, rdseed, adx, smap, xsaveopt, arat
Ecpus
10
Scalability
62.5

System Resources and Accelerators

MEMORY
Memory Amount
120 GiB
Memory Amount Actual
120 GiB
ACCELERATORS
Accelerator Count
2
Accelerator Memory Min
16 GiB
Accelerator Memory Total
32 GiB
Accelerator Type
GPU
Accelerator Manufacturer
NVIDIA
Accelerator Family
Pascal
Accelerator Model
P100
Accelerators
  • NVIDIA Pascal Tesla P100-PCIE-16GB (Memory amount: 16384, BIOS version: 86.00.41.00.06, Clock rate: 1328)
  • NVIDIA Pascal Tesla P100-PCIE-16GB (Memory amount: 16384, BIOS version: 86.00.41.00.06, Clock rate: 1328)
STORAGE
Storage Size
944 GB
Storage Type
ssd
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 GPU-accelerated virtual server featuring dual dedicated accelerators, local SSD storage, and balanced system memory for parallel computing workloads.

    GPU AcceleratedMemory OptimizedStorage & Database

    Alibaba Cloud ecs.gn5-c8g1.4xlarge is a GPU-accelerated instance designed for parallel computing workloads. It features 16 dedicated vCPUs from an Intel Xeon E5-2682 v4 processor running at 2.5 GHz, paired with 120.0 GB of system memory. The hardware configuration includes two NVIDIA Pascal P100 GPUs with a total of 32 GB VRAM, alongside a 944 GB local SSD and a 5 Gbps baseline network bandwidth. Benchmark data reveals modest single-core CPU performance, but stable multi-core and memory bandwidth capabilities, including a multi-core stress-ng score of 9532.02 and 10.88 million Redis SET operations per second. This instance is qualitatively cost-efficient for legacy GPU-accelerated tasks, scientific simulations, and database workloads that leverage dedicated hardware accelerators and local SSD storage rather than demanding high single-threaded CPU speeds.

    Economics

    Average Price per Region

    Prices per Zone

    Lowest Prices

    Performance

    Workload Profiles

    0.57Score
    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.Partial coverage: missing component benchmark(s): PassMark Memory Mark (composite), PassMark single-thread CPU.
    Component Score Weight Impact
    Raw Reference Normalized Target Actual
    Redis RPS (pipeline=1, SET) 1,148,876 ops/sec 1,919,289 ops/sec 0.58 50.00% 62.00% -29.00%
    Redis RPS (pipeline=16, SET) 6,819,829 ops/sec 11,728,058 ops/sec 0.57 20.00% 25.00% -13.00%
    PassMark Memory Mark (composite) — 2,416 — 10.00% 0.00% —
    Memory bandwidth (read, 16 MB ~ L3) 57,604 MB/sec 108,466 MB/sec 0.53 10.00% 13.00% -7.90%
    PassMark single-thread CPU — 2,365 Mops/s — 10.00% 0.00% —

    GPU Bandwidth and Latency

    Node (all GPUs)
    Node baseline directional bandwidth
    		10.5 GB/s
    Node GPU-to-host bandwidth
    		13.2 GB/s
    Node host-to-GPU bandwidth
    		10.6 GB/s
    Peer-to-peer
    GPU-to-GPU P2P duplex bandwidth
    		3.3 GB/s
    GPU-to-GPU P2P gather bandwidth
    		9.9 GB/s
    GPU-to-GPU P2P latency
    		1,609 ns
    GPU-to-GPU P2P bandwidth
    		9.9 GB/s
    Single GPU slot
    Per-GPU GPU-to-host bandwidth
    		13.2 GB/s
    Per-GPU host-to-GPU bandwidth
    		11.2 GB/s
    Per-GPU host-device latency
    		1,054 ns
    Benchmark Environment
    Driver Version
    		 580.159.03
    CUDA Runtime Version
    		 13.0
    nvbandwidth Version
    		 v0.8
    GPU Count
    		 6
    P2P Supported
    Yes
    Efficiency
    SM/CE copy efficiency
    		0.88

    Memory Bandwidth

    Compression

    OpenSSL

    Stress-ng Stressors

    CPU integerSingleMultiScaling
    atomic
    		 212.01 188.46 0.89×
    bitops
    		 101,096 872,600 8.63×
    branch
    		 132,189 1,560,978 11.81×
    funccall
    		 455.59 3,643 8.00×
    funcret
    		 8,884 104,671 11.78×
    hash
    		 108,070 1,280,288 11.85×
    intmath
    		 18,464 217,525 11.78×
    nop
    		 154,361 1,092,331 7.08×
    prime
    		 265,146 2,284,880 8.62×
    rotate
    		 83,573 869,120 10.40×
    str
    		 566,315 5,085,855 8.98×
    wcs
    		 377,396 3,217,870 8.53×
    CryptographySingleMultiScaling
    crypt
    		 1,972 15,275 7.75×
    CompressionSingleMultiScaling
    jpeg
    		 426.71 4,161 9.75×
    zlib
    		 42.22 546.45 12.94×
    HypervisorSingleMultiScaling
    clock
    		 24,631 215,521 8.75×
    clone
    		 423.18 2,602 6.15×
    context
    		 2,646 34,326 12.97×
    cpu-sched
    		 60.67 1,039 17.12×
    eventfd
    		 26,485 287,278 10.85×
    fault
    		 7,867 87,222 11.09×
    fork
    		 3,322 30,957 9.32×
    getrandom
    		 38,411 363,186 9.46×
    hrtimers
    		 306,345 1,751,610 5.72×
    mprotect
    		 958,891 2,814,208 2.93×
    mtx
    		 11,410,674 297,897,035 26.11×
    munmap
    		 2,308 23,967 10.39×
    null
    		 308,641 3,868,563 12.53×
    pipe
    		 847,129 5,004,584 5.91×
    priv-instr
    		 520,013 5,710,870 10.98×
    resched
    		 3,692,374 1,729,281 0.47×
    switch
    		 66,661 1,950,428 29.26×
    timermix
    		 212,445 2,658,520 12.51×
    tlb-shootdown
    		 9,655 30,296 3.14×
    tsc
    		 868,539 12,630,377 14.54×
    usersyscall
    		 357,004 4,081,360 11.43×
    vdso
    		 71,673,621 721,320,760 10.06×
    vfork
    		 16,573 133,373 8.05×
    x86syscall
    		 3,666,212 47,484,867 12.95×
    yield
    		 9,241,698 9,966,682 1.08×
    zero
    		 1,882,783 20,397,629 10.83×
    CPU float/SIMDSingleMultiScaling
    eigen
    		 12,666 125,660 9.92×
    expmath
    		 2,183 25,019 11.46×
    fma
    		 484,522 6,019,993 12.42×
    fp
    		 112.8 1,083 9.60×
    fractal
    		 4.4 44.8 10.18×
    hyperbolic
    		 2,472 29,637 11.99×
    logmath
    		 3,909 44,905 11.49×
    matrix
    		 3,029 27,500 9.08×
    matrix-3d
    		 608.91 2,254 3.70×
    monte-carlo
    		 139.86 1,718 12.28×
    mpfr
    		 993.95 8,125 8.17×
    powmath
    		 1,333 15,186 11.39×
    trig
    		 1,547 13,719 8.87×
    veccmp
    		 11,973 97,835 8.17×
    vecfp
    		 720.58 7,311 10.15×
    vecmath
    		 1,879 22,272 11.85×
    vecshuf
    		 470.53 3,979 8.46×
    vecwide
    		 19,126 167,780 8.77×
    AlgorithmsSingleMultiScaling
    bitonicsort
    		 6 56.6 9.43×
    bsearch
    		 194.33 1,887 9.71×
    bubblesort
    		 0.6 3.2 5.33×
    fibsearch
    		 234.45 2,279 9.72×
    heapsort
    		 7 64 9.14×
    hsearch
    		 3,781 33,750 8.93×
    insertionsort
    		 6.8 53.4 7.85×
    malloc
    		 1,546,136 22,780,030 14.73×
    mcontend
    		 121.32 3,579 29.50×
    mergesort
    		 22.4 238.19 10.63×
    qsort
    		 15.6 149.6 9.59×
    skiplist
    		 5,001 53,660 10.73×
    tree
    		 1 6.4 6.40×
    MemorySingleMultiScaling
    cache
    		 174,867 329,929 1.89×
    cachehammer
    		 448,211 5,980,113 13.34×
    cacheline
    		 37.15 660.12 17.77×
    l1cache
    		 164.67 1,309 7.95×
    memcpy
    		 361.79 3,007 8.31×
    memrate
    		 0.98 6.1 6.22×
    memthrash
    		 136.95 440.29 3.21×
    ptr-chase
    		 13,773,521 127,558,484 9.26×
    spinmem
    		 215.59 609.12 2.83×
    stream
    		 29.86 2,228 74.62×
    vm
    		 51,481 293,212 5.70×

    Stress-ng Raw Scores

    Stress-ng Relative Multicore Performance

    Static Web Server

    Redis

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    ecs.gn5-c8g1.4xlarge FAQs