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ecs.gn6v-c8g1.8xlarge by Alibaba Cloud

ecs.gn6v-c8g1.8xlarge is a ecs.gn6v family (32 vCPUs, 128 GiB RAM, 0 GB storage, 4xV100 16384.0 GiB VRAM) server offered by Alibaba Cloud with 32 vCPUs, 128 GiB of memory and 0 GB of storage. The pricing starts at 5.733 USD per hour.
32 vCPU
128 GiB Memory
4 GPU
Spare SCore
23576
(All-cores)
1104
(Single-core)

Specifications

Server Metadata

Vendor ID
alicloud
Name
ecs.gn6v-c8g1.8xlarge
Description
ecs.gn6v family (32 vCPUs, 128 GiB RAM, 0 GB storage, 4xV100 16384.0 GiB VRAM)
Family
ecs.gn6v
Hw Virt
Status
active
Observed At
2026-07-25T14:37:56.239689

Availability

REGION / IDSPOTONDEMAND
Beijing (CN) / cn-beijing
5.733 USD/h 16.38 USD/h
Qingdao (CN) / cn-qingdao
5.733 USD/h 16.38 USD/h
Shanghai (CN) / cn-shanghai
5.733 USD/h 16.38 USD/h
Hangzhou (CN) / cn-hangzhou
- 16.38 USD/h
Shenzhen (CN) / cn-shenzhen
- 16.38 USD/h

Processor

vCPUs
32
Hypervisor
KVM
CPU Allocation
Dedicated
CPU Cores
32
CPU Speed
2.5 GHz
CPU Architecture
x86_64
CPU Manufacturer
Intel
CPU Family
Xeon
CPU Model
8163
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
33 MiB
CPU L3 Cache Total
33 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, nonstop_tsc, cpuid, tsc_known_freq, pni, pclmulqdq, monitor, ssse3, cx16, pcid, sse4_1, sse4_2, x2apic, movbe, popcnt, tsc_deadline_timer, aes, f16c, rdrand, hypervisor, lahf_lm, abm, 3dnowprefetch, pti, ibrs, ibpb, stibp, fsgsbase, tsc_adjust, bmi1, hle, smep, bmi2, erms, invpcid, rtm, rdseed, adx, smap, arat
Ecpus
21.4
Scalability
66.88

System Resources and Accelerators

MEMORY
Memory Amount
128 GiB
Memory Amount Actual
128 GiB
GPU
GPU Count
4
GPU Memory Min
16 GiB
GPU Memory Total
64 GiB
GPU Manufacturer
NVIDIA
GPU Family
Volta
GPU Model
V100
GPUs
  • NVIDIA Volta Tesla V100-SXM2-16GB (Memory amount: 16384, BIOS version: 88.00.4F.00.09, Clock rate: 1530)
  • NVIDIA Volta Tesla V100-SXM2-16GB (Memory amount: 16384, BIOS version: 88.00.4F.00.09, Clock rate: 1530)
  • NVIDIA Volta Tesla V100-SXM2-16GB (Memory amount: 16384, BIOS version: 88.00.4F.00.09, Clock rate: 1530)
  • NVIDIA Volta Tesla V100-SXM2-16GB (Memory amount: 16384, BIOS version: 88.00.4F.00.09, Clock rate: 1530)
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 multi-GPU accelerated platform featuring four dedicated graphics processors and thirty-two physical cores for parallel computing workloads.

    GPU AcceleratedGeneral Purpose

    Alibaba Cloud ecs.gn6v-c8g1.8xlarge is a GPU-accelerated instance featuring 32 dedicated physical cores on an Intel Xeon 8163 processor running at 2.5 GHz. Built on the x86_64 architecture and KVM hypervisor, it is equipped with 128.0 GB of RAM and four NVIDIA Volta V100 GPUs providing 64 GB of total VRAM. The instance does not include local storage and relies on a 10 Gbps baseline network bandwidth. Benchmark data shows weak single-core CPU performance but average multi-core and memory bandwidth capabilities, with PassMark CPU and multi-threaded bzip3 decompression scores landing in the middle 50%. This hardware profile is qualitatively cost-efficient for parallel computing tasks that leverage multi-GPU setups rather than single-threaded CPU speed. It is suited for deep learning, parallel simulations, and GPU-accelerated data processing.

    Economics

    Average Price per Region

    Prices per Zone

    Lowest Prices

    Performance

    Workload Profiles

    0.999Score
    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) 1,909,466 ops/sec 1,896,415 ops/sec 1.01 50.00% 50.00% +0.50%
    Redis RPS (pipeline=16, SET) 13,530,634 ops/sec 11,539,523 ops/sec 1.17 20.00% 20.00% +3.19%
    PassMark Memory Mark (composite) 1,888 2,411 0.783 10.00% 10.00% -2.42%
    Memory bandwidth (read, 16 MB ~ L3) 129,070 MB/sec 107,368 MB/sec 1.2 10.00% 10.00% +1.84%
    PassMark single-thread CPU 1,741 Mops/s 2,363 Mops/s 0.737 10.00% 10.00% -3.01%

    Memory Bandwidth

    Compression

    OpenSSL

    Passmark CPU Scores

    BENCHMARKSCORE
    Mark
    		 21093
    Compression
    		 363131
    Encryption
    		 10928
    Extended Instructions
    		 9124
    Floating Point Maths
    		 48433
    Integer Maths
    		 78760
    Physics
    		 2505
    Prime Numbers
    		 142
    Single Threaded
    		 1741
    String Sorting
    		 49019

    Passmark Memory Scores

    BENCHMARKSCORE
    Memory Mark
    		 1888
    Database Operations
    		 8321
    Memory Latency
    		 77
    Memory Read Cached
    		 19346
    Memory Read Uncached
    		 7032
    Memory Write
    		 7365

    Stress-ng Raw Scores

    Stress-ng Relative Multicore Performance

    Static Web Server

    Redis

    Alternatives

    Servers of the Same Family

    INSTANCEvCPUsMEMORYGPUs
    ecs.gn6v-c8g1.2xlarge 832 GiB1
    ecs.gn6v-c8g1.4xlarge 1664 GiB2
    ecs.gn6v-c8g1.16xlarge 64256 GiB8
    ecs.gn6v-c10g1.20xlarge 82336 GiB8

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    ecs.gn6v-c8g1.8xlarge FAQs