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ecs.sn1.7xlarge by Alibaba Cloud

ecs.sn1.7xlarge is a ecs.sn1 family (32 vCPUs, 64 GiB RAM, 0 GB storage) server offered by Alibaba Cloud with 32 vCPUs, 64 GiB of memory and 0 GB of storage. The pricing starts at 0.1468 USD per hour.
32 vCPU
64 GiB Memory
Spare SCore
23558
(All-cores)
1110
(Single-core)

Specifications

Server Metadata

Vendor ID
alicloud
Name
ecs.sn1.7xlarge
Description
ecs.sn1 family (32 vCPUs, 64 GiB RAM, 0 GB storage)
Family
ecs.sn1
Hw Virt
Status
active
Observed At
2026-07-30T12:03:08.373192

Availability

REGION / IDSPOTONDEMAND
Singapore (SG) / ap-southeast-1
- 1.57 USD/h
Beijing (CN) / cn-beijing
0.1468 USD/h 2.097 USD/h
Jakarta (ID) / ap-southeast-5
0.2097 USD/h 2.097 USD/h
Hangzhou (CN) / cn-hangzhou
0.2516 USD/h 2.097 USD/h
Shanghai (CN) / cn-shanghai
- 2.097 USD/h
Shenzhen (CN) / cn-shenzhen
- 2.097 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, 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, mpx, avx512f, avx512dq, rdseed, adx, smap, avx512cd, avx512bw, avx512vl, xsaveopt, xsavec, xgetbv1, arat
Ecpus
21.2
Scalability
66.25

System Resources and Accelerators

MEMORY
Memory Amount
64 GiB
Memory Amount Actual
64 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
      6 Gbps
      Inbound Traffic
      0 GB/month
      Outbound Traffic
      0 GB/month
      IPv4
      0

      CPU and System Topology

      Server Description

      A compute-optimized server featuring thirty-two dedicated cores and a balanced multi-threaded performance profile for parallelized workloads.

      Compute Optimized

      Alibaba Cloud ecs.sn1.7xlarge is an x86_64 compute-optimized server instance featuring 32 dedicated Intel Xeon 8163 vCPUs running at 2.5 GHz and 64.0 GB of RAM. Lacking local storage and GPU hardware, it relies on a 6 Gbps baseline network bandwidth. Benchmarks reveal a significant performance divergence: single-core metrics, including Geekbench and stress-ng single-core tests, fall into the bottom 25%, whereas multi-core benchmarks, such as PassMark CPU and bzip3 multi-threaded decompression, achieve average tier results. This hardware profile, with its 1:2 vCPU-to-RAM ratio, offers qualitative cost efficiency for highly parallelized workloads that are not memory-constrained. It is suited for multi-threaded tasks like software compilation, static web serving, and moderate database operations, but represents a poor fit for single-threaded applications or memory-heavy workloads.

      Economics

      Average Price per Region

      Prices per Zone

      Lowest Prices

      Performance

      Workload Profiles

      0.93Score
      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) 1,866,822 ops/sec 1,896,415 ops/sec 0.984 50.00% 50.00% -0.80%
      Redis RPS (pipeline=16, SET) 13,278,938 ops/sec 11,539,523 ops/sec 1.15 20.00% 20.00% +2.83%
      PassMark Memory Mark (composite) 1,810 2,411 0.751 10.00% 10.00% -2.82%
      Memory bandwidth (read, 16 MB ~ L3) 79,057 MB/sec 107,368 MB/sec 0.736 10.00% 10.00% -3.02%
      PassMark single-thread CPU 1,693 Mops/s 2,363 Mops/s 0.716 10.00% 10.00% -3.29%

      Memory Bandwidth

      Compression

      OpenSSL

      Geekbench Single-Core

      Score: 960

      Geekbench Multi-Core

      Score: 8,426

      Passmark CPU Scores

      BENCHMARKSCORE
      Mark
      		 22982
      Compression
      		 366076
      Encryption
      		 10872
      Extended Instructions
      		 23772
      Floating Point Maths
      		 42262
      Integer Maths
      		 78750
      Physics
      		 2039
      Prime Numbers
      		 104
      Single Threaded
      		 1693
      String Sorting
      		 46446

      Passmark Memory Scores

      BENCHMARKSCORE
      Memory Mark
      		 1810
      Database Operations
      		 8482
      Memory Latency
      		 81
      Memory Read Cached
      		 19392
      Memory Read Uncached
      		 6847
      Memory Write
      		 7324

      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.sn1.medium 24 GiB0
      ecs.sn1.large 48 GiB0
      ecs.sn1.xlarge 816 GiB0
      ecs.sn1.3xlarge 1632 GiB0

      Similar Servers

      INSTANCEVENDORvCPUsMEMORYGPUs

      ecs.sn1.7xlarge FAQs