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ecs.c7.3xlarge by Alibaba Cloud

ecs.c7.3xlarge is a ecs.c7 family (12 vCPUs, 24 GiB RAM, 0 GB storage) server offered by Alibaba Cloud with 12 vCPUs, 24 GiB of memory and 0 GB of storage. The pricing starts at 0.064 USD per hour.
12 vCPU
24 GiB Memory
Spare SCore
11645
(All-cores)
1875
(Single-core)

Specifications

Server Metadata

Vendor ID
alicloud
Name
ecs.c7.3xlarge
Description
ecs.c7 family (12 vCPUs, 24 GiB RAM, 0 GB storage)
Family
ecs.c7
Hw Virt
Status
active
Observed At
2026-07-25T22:25:02.972408

Availability

REGION / IDSPOTONDEMAND
Heyuan (CN) / cn-heyuan
0.064 USD/h 0.337 USD/h
Ulanqab (CN) / cn-wulanchabu
0.079533 USD/h 0.3408 USD/h
Guangzhou (CN) / cn-guangzhou
- 0.3786 USD/h
Hangzhou (CN) / cn-hangzhou
- 0.3786 USD/h
Shanghai (CN) / cn-shanghai
- 0.3786 USD/h
Shenzhen (CN) / cn-shenzhen
- 0.3786 USD/h
Fuzhou (CN) / cn-fuzhou
- 0.3787 USD/h
Virginia (US) / us-east-1
0.11015 USD/h 0.459 USD/h
Frankfurt (DE) / eu-central-1
0.0996 USD/h 0.524 USD/h
Tokyo (JP) / ap-northeast-1
0.1098 USD/h 0.578 USD/h
Hong Kong (HK) / cn-hongkong
0.1516 USD/h 0.5832 USD/h

Processor

vCPUs
12
Hypervisor
KVM
CPU Allocation
Dedicated
CPU Cores
12
CPU Speed
2.7 GHz
CPU Architecture
x86_64
CPU Manufacturer
Intel
CPU Family
Xeon
CPU Model
8369B
CPU L1D Cache
48 KiB
CPU L1D Cache Total
288 KiB
CPU L1I Cache
32 KiB
CPU L1I Cache Total
192 KiB
CPU L2 Cache
1 MiB
CPU L2 Cache Total
8 MiB
CPU L3 Cache
48 MiB
CPU L3 Cache Total
48 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, cpuid_fault, ibrs_enhanced, fsgsbase, tsc_adjust, bmi1, avx2, smep, bmi2, erms, invpcid, avx512f, avx512dq, rdseed, adx, smap, avx512ifma, clflushopt, clwb, avx512cd, sha_ni, avx512bw, avx512vl, xsaveopt, xsavec, xgetbv1, xsaves, wbnoinvd, arat, avx512vbmi, pku, ospke, avx512_vbmi2, gfni, vaes, vpclmulqdq, avx512_vnni, avx512_bitalg, avx512_vpopcntdq, rdpid, fsrm, arch_capabilities
Ecpus
6.2
Scalability
51.67

System Resources and Accelerators

MEMORY
Memory Amount
24 GiB
Memory Amount Actual
24 GiB
GPU
GPU Count
0
GPU Memory Min
0 MiB
GPU Memory Total
0 MiB
GPUs
    STORAGE
    Storage Size
    0 GB
    Storages
      NETWORK
      Network Speed Baseline
      8 Gbps
      Inbound Traffic
      0 GB/month
      Outbound Traffic
      0 GB/month
      IPv4
      0

      CPU and System Topology

      Server Description

      A dedicated twelve-core compute-optimized instance designed for high-throughput web serving, software compilation, and lightweight vector-accelerated workloads.

      Compute OptimizedGeneral Purpose

      Alibaba Cloud ecs.c7.3xlarge is a compute-optimized instance featuring 12 dedicated vCPUs on an Intel Xeon 8369B processor running at 2.7 GHz, paired with 24.0 GB of RAM. Operating on the x86_64 architecture under the KVM hypervisor, this instance lacks local storage and GPU accelerators but provides a baseline network bandwidth of 8 Gbps. Benchmark results place its performance in the average range, with a Geekbench multi-core score of 7760.0 and a Passmark CPU score of 16209.01. It delivers strong throughput for static web serving at 15.7 GB/sec and handles 11.74 million Redis SET operations per second. The instance is highly suitable for compute-intensive workloads such as software compilation, web serving, and lightweight machine learning inference, offering a balanced, cost-efficient resource density for dedicated CPU tasks.

      Economics

      Average Price per Region

      Prices per Zone

      Lowest Prices

      Performance

      Workload Profiles

      0.804Score
      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) 1,533,575 ops/sec 1,896,415 ops/sec 0.809 50.00% 50.00% -10.10%
      Redis RPS (pipeline=16, SET) 7,874,509 ops/sec 11,539,523 ops/sec 0.682 20.00% 20.00% -7.37%
      PassMark Memory Mark (composite) 2,304 2,411 0.956 10.00% 10.00% -0.45%
      Memory bandwidth (read, 16 MB ~ L3) 79,009 MB/sec 107,368 MB/sec 0.736 10.00% 10.00% -3.02%
      PassMark single-thread CPU 2,361 Mops/s 2,363 Mops/s 0.999 10.00% 10.00% -0.01%

      Memory Bandwidth

      Compression

      OpenSSL

      Geekbench Single-Core

      Score: 1,531

      Geekbench Multi-Core

      Score: 7,760

      Passmark CPU Scores

      BENCHMARKSCORE
      Mark
      		 16209
      Compression
      		 184953
      Encryption
      		 10958
      Extended Instructions
      		 10514
      Floating Point Maths
      		 25820
      Integer Maths
      		 50488
      Physics
      		 1691
      Prime Numbers
      		 87
      Single Threaded
      		 2361
      String Sorting
      		 26005

      Passmark Memory Scores

      BENCHMARKSCORE
      Memory Mark
      		 2304
      Database Operations
      		 5803
      Memory Latency
      		 57
      Memory Read Cached
      		 24213
      Memory Read Uncached
      		 10742
      Memory Write
      		 9828

      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
      ecs.c7.large 24 GiB0
      ecs.c7.xlarge 48 GiB0
      ecs.c7.2xlarge 816 GiB0
      ecs.c7.4xlarge 1632 GiB0
      ecs.c7.6xlarge 2448 GiB0
      ecs.c7.8xlarge 3264 GiB0
      ecs.c7.16xlarge 64128 GiB0

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      ecs.c7.3xlarge FAQs