ecs.u1-c1m2.4xlarge by Alibaba Cloud

ecs.u1-c1m2.4xlarge is a ecs.u1 family (16 vCPUs, 32 GiB RAM, 0 GB storage) server offered by Alibaba Cloud with 16 vCPUs, 32 GiB of memory and 0 GB of storage. The pricing starts at 0.0304 USD per hour.
16 vCPU
32 GiB Memory
Spare SCore
15,441
(All-cores)
1,877
(Single-core)

Specifications

Server Metadata

Vendor ID
alicloud
Name
ecs.u1-c1m2.4xlarge
Description
ecs.u1 family (16 vCPUs, 32 GiB RAM, 0 GB storage)
Family
ecs.u1
Hw Virt
Status
active
Observed At
2026-09-18T23:14:33.667317

Availability

REGION / IDSPOTONDEMAND
Heyuan (CN) / cn-heyuan
0.0304 USD/h 0.3037 USD/h
Ulanqab (CN) / cn-wulanchabu
- 0.3037 USD/h
Chengdu (CN) / cn-chengdu
0.0435 USD/h 0.4347 USD/h
Guangzhou (CN) / cn-guangzhou
0.0435 USD/h 0.4347 USD/h
Hangzhou (CN) / cn-hangzhou
0.0435 USD/h 0.4347 USD/h
Qingdao (CN) / cn-qingdao
0.06305 USD/h 0.4347 USD/h
Shenzhen (CN) / cn-shenzhen
0.0435 USD/h 0.4347 USD/h
Beijing (CN) / cn-beijing
0.0609 USD/h 0.4347 USD/h
Shanghai (CN) / cn-shanghai
0.0652 USD/h 0.4347 USD/h
Silicon Valley (US) / us-west-1
0.134 USD/h 0.5582 USD/h
Frankfurt (DE) / eu-central-1
0.0632 USD/h 0.6318 USD/h
Singapore (SG) / ap-southeast-1
0.1541 USD/h 0.6422 USD/h
London (GB) / eu-west-1
0.1094 USD/h 0.663 USD/h
Hong Kong (HK) / cn-hongkong
0.0706 USD/h 0.7055 USD/h

Processor

vCPUs
16
Hypervisor
KVM
CPU Allocation
Dedicated
CPU Cores
16
CPU Speed
2.5 GHz
CPU Architecture
x86_64
CPU Manufacturer
Intel
CPU Family
Xeon
CPU L1D Cache
32 KiB
CPU L1D Cache Total
256 KiB
CPU L1I Cache
32 KiB
CPU L1I Cache Total
256 KiB
CPU L2 Cache
1 MiB
CPU L2 Cache Total
8 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, cpuid_fault, 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
8.2
Scalability
51.25

System Resources and Accelerators

MEMORY
Memory Amount
32 GiB
Memory Amount Actual
32 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
      5 Gbps
      Inbound Traffic
      0 GB/month
      Outbound Traffic
      0 GB/month
      IPv4
      0

      CPU and System Topology

      Server Description

      A dedicated 16-core compute-optimized server designed for multi-threaded processing, software compilation, and high-throughput web serving without local storage overhead.

      Compute OptimizedGeneral Purpose

      Alibaba Cloud ecs.u1-c1m2.4xlarge is an x86_64 compute-optimized server featuring 16 dedicated Intel Xeon physical cores running at 2.5 GHz and 32.0 GB of RAM. Operating on a KVM hypervisor, this instance provides a 1:2 vCPU-to-RAM ratio and a baseline network bandwidth of 5 Gbps, without bundled local storage or GPUs. Benchmark results place its performance in the average tier, with a multi-core stress-ng score of 15440.75 and a Geekbench compilation score of 14533.0. It delivers a static web serving throughput of 16.69 GB/sec and handles 15.82 million Redis SET operations per second. This hardware profile is qualitatively cost-efficient for compute-focused workloads that do not require massive memory footprints. It is well-suited for software compilation, web serving, multi-threaded processing, and lightweight machine learning inference.

      Economics

      Average Price per Region

      Prices per Zone

      Lowest Prices

      Performance

      Workload Profiles

      0.886Score
      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) 1,702,791 ops/sec 1,919,696 ops/sec 0.887 50.00% 50.00% -5.82%
      Redis RPS (pipeline=16, SET) 9,886,335 ops/sec 11,736,081 ops/sec 0.842 20.00% 20.00% -3.38%
      PassMark Memory Mark (composite) 2,310 2,418 0.955 10.00% 10.00% -0.46%
      Memory bandwidth (read, 16 MB ~ L3) 87,412 MB/sec 108,260 MB/sec 0.807 10.00% 10.00% -2.12%
      PassMark single-thread CPU 2,348 Mops/s 2,365 Mops/s 0.993 10.00% 10.00% -0.07%

      Memory Bandwidth

      Compression

      OpenSSL

      Geekbench Single-Core

      Score: 1,402

      Geekbench Multi-Core

      Score: 8,470

      Passmark CPU Scores

      BENCHMARKSCORE
      Mark
      		 19227
      Compression
      		 246166
      Encryption
      		 8468
      Extended Instructions
      		 13985
      Floating Point Maths
      		 34269
      Integer Maths
      		 66944
      Physics
      		 1859
      Prime Numbers
      		 120
      Single Threaded
      		 2348
      String Sorting
      		 34312

      Passmark Memory Scores

      BENCHMARKSCORE
      Memory Mark
      		 2310
      Database Operations
      		 7794
      Memory Latency
      		 54
      Memory Read Cached
      		 23896
      Memory Read Uncached
      		 8816
      Memory Write
      		 8827

      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.u1-c1m1.large 22 GiB0
      ecs.u1-c1m2.large 24 GiB0
      ecs.u1-c1m4.large 28 GiB0
      ecs.u1-c1m8.large 216 GiB0
      ecs.u1-c1m1.xlarge 44 GiB0
      ecs.u1-c1m2.xlarge 48 GiB0
      ecs.u1-c1m4.xlarge 416 GiB0

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      ecs.u1-c1m2.4xlarge FAQs