a2-highgpu-2g by Google Cloud Platform

a2-highgpu-2g is a Accelerator Optimized: 2 NVIDIA Tesla A100 GPUs, 24 vCPUs, 170GB RAM server offered by Google Cloud Platform with 24 vCPUs, 170 GiB of memory and 0 GB of storage. The pricing starts at 4.1854 USD per hour.
24 vCPU
170 GiB Memory
2 GPU
Spare SCore
18,976
(All-cores)
1,202
(Single-core)

Specifications

Server Metadata

Vendor ID
gcp
Server ID
1000024
Name
a2-highgpu-2g
Description
Accelerator Optimized: 2 NVIDIA Tesla A100 GPUs, 24 vCPUs, 170GB RAM
Family
a2
Hw Virt
Average Time To Start
57
Status
active
Observed At
2026-09-20T23:06:34.492698

Availability

REGION / IDSPOTONDEMAND
Council Bluffs (US) / us-central1
4.408 USD/h 7.3468 USD/h
The Dalles (US) / us-west1
4.408 USD/h 7.3468 USD/h
Moncks Corner (US) / us-east1
4.408 USD/h 7.3468 USD/h
Eemshaven (NL) / europe-west4
4.4966 USD/h 7.4959 USD/h
Las Vegas (US) / us-west4
4.1854 USD/h 7.8687 USD/h
Jurong West (SG) / asia-southeast1
4.8045 USD/h 8.0275 USD/h
Tel Aviv (IL) / me-west1
4.8488 USD/h 8.0814 USD/h
Tokyo (JP) / asia-northeast1
4.8472 USD/h 8.0992 USD/h
Seoul (KR) / asia-northeast3
4.8472 USD/h 8.0992 USD/h
Salt Lake City (US) / us-west3
5.1769 USD/h 8.6501 USD/h

Processor

vCPUs
24
CPU Allocation
Dedicated
CPU Cores
12
CPU Speed
2.2 GHz
CPU Architecture
x86_64
CPU Manufacturer
Intel
CPU Family
Xeon
CPU L1D Cache
32 KiB
CPU L1D Cache Total
384 KiB
CPU L1I Cache
32 KiB
CPU L1I Cache Total
384 KiB
CPU L2 Cache
1 MiB
CPU L2 Cache Total
12 MiB
CPU L3 Cache
39 MiB
CPU L3 Cache Total
39 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, aes, xsave, avx, f16c, rdrand, hypervisor, lahf_lm, abm, 3dnowprefetch, ssbd, ibrs, ibpb, stibp, ibrs_enhanced, fsgsbase, tsc_adjust, bmi1, hle, avx2, smep, bmi2, erms, invpcid, rtm, mpx, avx512f, avx512dq, rdseed, adx, smap, clflushopt, clwb, avx512cd, avx512bw, avx512vl, xsaveopt, xsavec, xgetbv1, xsaves, arat, avx512_vnni, md_clear, arch_capabilities
Ecpus
15.8
Scalability
131.67

System Resources and Accelerators

MEMORY
Memory Amount
170 GiB
Memory Amount Actual
170 GiB
GPU
GPU Count
2
GPU Memory Min
40 GiB
GPU Memory Total
80 GiB
GPU Manufacturer
NVIDIA
GPU Family
Ampere
GPU Model
A100
GPUs
  • NVIDIA Ampere NVIDIA A100-SXM4-40GB (Memory amount: 40960, Firmware version: 590.48.01, BIOS version: 92.00.45.00.03, Clock rate: 1410)
  • NVIDIA Ampere NVIDIA A100-SXM4-40GB (Memory amount: 40960, Firmware version: 590.48.01, BIOS version: 92.00.45.00.03, Clock rate: 1410)
STORAGE
Storage Size
0 GB
Storages
    NETWORK
    Inbound Traffic
    0 GB/month
    Outbound Traffic
    0 GB/month
    IPv4
    0

    CPU and System Topology

    Server Description

    An accelerator-optimized platform pairing dual NVIDIA A100 GPUs with 170 GB of memory for high-throughput parallel computing and LLM inference.

    GPU AcceleratedMemory Optimized

    Google Cloud Platform a2-highgpu-2g is an accelerator-optimized server configured with two NVIDIA Ampere A100 GPUs providing 80 GB of total VRAM, 24 vCPUs on an Intel Xeon x86_64 processor, and 170.0 GB of system memory. It does not include local storage. Performance benchmarks indicate a distinct tradeoff: single-core CPU execution is relatively weak, scoring in the bottom 25%, and multi-core CPU performance is average. However, the instance delivers top-tier performance in LLM inference benchmarks, particularly for prompt processing and text generation on medium to large models. Qualitatively, the high resource density of GPUs and memory makes this instance cost-efficient for specialized parallel workloads rather than general-purpose compute. It is highly suited for deep learning, large language model inference, and GPU-accelerated data science tasks.

    Economics

    Average Price per Region

    Prices per Zone

    Lowest Prices

    Performance

    Workload Profiles

    0.951Score
    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) 1,844,266 ops/sec 1,919,696 ops/sec 0.961 50.00% 50.00% -1.97%
    Redis RPS (pipeline=16, SET) 11,433,281 ops/sec 11,736,081 ops/sec 0.974 20.00% 20.00% -0.53%
    PassMark Memory Mark (composite) 2,483 2,418 1.03 10.00% 10.00% +0.30%
    Memory bandwidth (read, 16 MB ~ L3) 114,321 MB/sec 108,260 MB/sec 1.06 10.00% 10.00% +0.58%
    PassMark single-thread CPU 1,693 Mops/s 2,365 Mops/s 0.716 10.00% 10.00% -3.29%

    Memory Bandwidth

    Compression

    OpenSSL

    Geekbench Single-Core

    Score: 1,066

    Geekbench Multi-Core

    Score: 8,247

    Passmark CPU Scores

    BENCHMARKSCORE
    Mark
    19022
    Compression
    278622
    Encryption
    8685
    Extended Instructions
    18027
    Floating Point Maths
    34100
    Integer Maths
    63469
    Physics
    1952
    Prime Numbers
    102
    Single Threaded
    1693
    String Sorting
    32865

    Passmark Memory Scores

    BENCHMARKSCORE
    Memory Mark
    2483
    Database Operations
    7693
    Memory Latency
    56
    Memory Read Cached
    20838
    Memory Read Uncached
    10561
    Memory Write
    9923

    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

    INSTANCEvCPUsMEMORYGPUs
    a2-highgpu-1g 1285 GiB1
    a2-ultragpu-1g 12170 GiB1
    a2-ultragpu-2g 24340 GiB2
    a2-highgpu-4g 48340 GiB4
    a2-ultragpu-4g 48680 GiB4
    a2-highgpu-8g 96680 GiB8
    a2-ultragpu-8g 961360 GiB8

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    a2-highgpu-2g FAQs