ecs.gn6i-c40g1.10xlarge by Alibaba Cloud

ecs.gn6i-c40g1.10xlarge is a ecs.gn6i family (40 vCPUs, 155 GiB RAM, 0 GB storage, 1xT4 16384.0 GiB VRAM) server offered by Alibaba Cloud with 40 vCPUs, 155 GiB of memory and 0 GB of storage. The pricing starts at 0.3286 USD per hour.
40 vCPU
155 GiB Memory
1 GPU
Spare SCore
29,538
(All-cores)
1,107
(Single-core)

Specifications

Server Metadata

Vendor ID
alicloud
Name
ecs.gn6i-c40g1.10xlarge
Description
ecs.gn6i family (40 vCPUs, 155 GiB RAM, 0 GB storage, 1xT4 16384.0 GiB VRAM)
Family
ecs.gn6i
Hw Virt
Status
active
Observed At
2026-09-10T13:32:25.581651

Availability

REGION / IDSPOTONDEMAND
Chengdu (CN) / cn-chengdu
0.6902 USD/h 1.972 USD/h
Ulanqab (CN) / cn-wulanchabu
0.6902 USD/h 1.972 USD/h
Qingdao (CN) / cn-qingdao
0.54775 USD/h 2.191 USD/h
Shanghai (CN) / cn-shanghai
0.7669 USD/h 2.191 USD/h
Beijing (CN) / cn-beijing
- 2.191 USD/h
Guangzhou (CN) / cn-guangzhou
- 2.191 USD/h
Hangzhou (CN) / cn-hangzhou
- 2.191 USD/h
Shenzhen (CN) / cn-shenzhen
- 2.191 USD/h
Virginia (US) / us-east-1
1.0631 USD/h 3.0375 USD/h
Hong Kong (HK) / cn-hongkong
- 3.2952 USD/h
Singapore (SG) / ap-southeast-1
1.214 USD/h 3.4686 USD/h
Jakarta (ID) / ap-southeast-5
- 3.4686 USD/h
Tokyo (JP) / ap-northeast-1
0.8913 USD/h 3.5651 USD/h

Processor

vCPUs
40
Hypervisor
KVM
CPU Allocation
Dedicated
CPU Cores
40
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
640 KiB
CPU L1I Cache
32 KiB
CPU L1I Cache Total
640 KiB
CPU L2 Cache
1 MiB
CPU L2 Cache Total
20 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, xtopology, nonstop_tsc, cpuid, 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, arat
Ecpus
26.7
Scalability
66.75

System Resources and Accelerators

MEMORY
Memory Amount
155 GiB
Memory Amount Actual
155 GiB
GPU
GPU Count
1
GPU Memory Min
16 GiB
GPU Memory Total
16 GiB
GPU Manufacturer
NVIDIA
GPU Family
Turing
GPU Model
T4
GPUs
  • NVIDIA Turing Tesla T4 (Memory amount: 15360, Firmware version: 590.48.01, BIOS version: 90.04.38.00.03, Clock rate: 1590)
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 GPU-accelerated instance combining forty dedicated Intel Xeon cores with an NVIDIA T4 GPU for efficient machine learning inference workloads.

    GPU AcceleratedGeneral Purpose

    Alibaba Cloud ecs.gn6i-c40g1.10xlarge is an x86_64 GPU-accelerated instance featuring 40 dedicated Intel Xeon 8163 cores running at 2.5 GHz, 155.0 GB of RAM, and a single NVIDIA T4 GPU with 16 GB of VRAM. Operating on the KVM hypervisor, this instance does not include local storage and relies on a 10 Gbps baseline network connection. Benchmark data reveals weak single-core CPU performance, but average multi-core scaling and memory bandwidth. Notably, the instance delivers top-tier performance in LLM prompt processing for small and medium models, and strong text generation speeds for 7B models. This hardware profile is qualitatively cost-effective for GPU-accelerated tasks, making it well-suited for machine learning inference, parallel data processing, and video transcoding, though it is less efficient for single-threaded workloads or those requiring local SSD storage.

    Economics

    Average Price per Region

    Prices per Zone

    Lowest Prices

    Performance

    Workload Profiles

    1.27Score
    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) 3,087,352 ops/sec 1,917,397 ops/sec 1.61 50.00% 50.00% +26.90%
    Redis RPS (pipeline=16, SET) 16,513,797 ops/sec 11,681,410 ops/sec 1.41 20.00% 20.00% +7.11%
    PassMark Memory Mark (composite) 1,856 2,418 0.768 10.00% 10.00% -2.61%
    Memory bandwidth (read, 16 MB ~ L3) 105,001 MB/sec 108,140 MB/sec 0.971 10.00% 10.00% -0.29%
    PassMark single-thread CPU 1,664 Mops/s 2,365 Mops/s 0.704 10.00% 10.00% -3.45%

    Memory Bandwidth

    Compression

    OpenSSL

    Geekbench Single-Core

    Score: 934

    Geekbench Multi-Core

    Score: 9,161

    Passmark CPU Scores

    BENCHMARKSCORE
    Mark
    		 27269
    Compression
    		 451006
    Encryption
    		 13602
    Extended Instructions
    		 29377
    Floating Point Maths
    		 52975
    Integer Maths
    		 98856
    Physics
    		 2549
    Prime Numbers
    		 126
    Single Threaded
    		 1664
    String Sorting
    		 58224

    Passmark Memory Scores

    BENCHMARKSCORE
    Memory Mark
    		 1856
    Database Operations
    		 10680
    Memory Latency
    		 78
    Memory Read Cached
    		 19440
    Memory Read Uncached
    		 6652
    Memory Write
    		 7184

    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

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    INSTANCEvCPUsMEMORYGPUs
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    ecs.gn6i-c24g1.6xlarge 2493 GiB1
    ecs.gn6i-c24g1.12xlarge 48186 GiB2
    ecs.gn6i-c24g1.24xlarge 96372 GiB4

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    ecs.gn6i-c40g1.10xlarge FAQs