CLOUDNATIVE-16xCPU-128GB by UpCloud

CLOUDNATIVE-16xCPU-128GB is a Cloud Native (16 vCPUs, 128 GiB RAM) server offered by UpCloud with 16 vCPUs, 128 GiB of memory and 0 GB of storage. The pricing starts at 0.6396 USD per hour.
16 vCPU
128 GiB Memory
Spare SCore
59,283
(All-cores)
3,860
(Single-core)

Specifications

Server Metadata

Vendor ID
upcloud
Name
CLOUDNATIVE-16xCPU-128GB
Description
Cloud Native (16 vCPUs, 128 GiB RAM)
Family
Cloud Native
Hw Virt
Average Time To Start
120
Status
active
Observed At
2026-09-10T14:30:16.251669

Availability

REGION / IDSPOTONDEMAND
Sydney #1 (AU) / au-syd1
- 0.6396 USD/h
Frankfurt #1 (DE) / de-fra1
- 0.6396 USD/h
Copenhagen #1 (DK) / dk-cph1
- 0.6396 USD/h
Madrid #1 (ES) / es-mad1
- 0.6396 USD/h
Helsinki #1 (FI) / fi-hel1
- 0.6396 USD/h
Helsinki #2 (FI) / fi-hel2
- 0.6396 USD/h
Amsterdam #1 (NL) / nl-ams1
- 0.6396 USD/h
Stavanger #1 (NO) / no-svg1
- 0.6396 USD/h
Warsaw #1 (PL) / pl-waw1
- 0.6396 USD/h
Stockholm #1 (SE) / se-sto1
- 0.6396 USD/h
Singapore #1 (SG) / sg-sin1
- 0.6396 USD/h
London #1 (GB) / uk-lon1
- 0.6396 USD/h
Chicago #1 (US) / us-chi1
- 0.6396 USD/h
New York #1 (US) / us-nyc1
- 0.6396 USD/h
San Jose #1 (US) / us-sjo1
- 0.6396 USD/h

Processor

vCPUs
16
Hypervisor
KVM
CPU Allocation
Shared
CPU Cores
16
CPU Speed
2 GHz
CPU Architecture
x86_64
CPU Manufacturer
AMD
CPU Family
EPYC
CPU Model
9575F
CPU L1D Cache
64 KiB
CPU L1D Cache Total
1 MiB
CPU L1I Cache
64 KiB
CPU L1I Cache Total
1 MiB
CPU L2 Cache
512 KiB
CPU L2 Cache Total
8 MiB
CPU L3 Cache
16 MiB
CPU L3 Cache Total
16 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, ht, syscall, nx, mmxext, fxsr_opt, pdpe1gb, rdtscp, lm, rep_good, nopl, cpuid, extd_apicid, 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, cmp_legacy, cr8_legacy, abm, sse4a, misalignsse, 3dnowprefetch, osvw, perfctr_core, ssbd, ibrs, ibpb, stibp, vmmcall, fsgsbase, tsc_adjust, bmi1, avx2, smep, bmi2, invpcid, avx512f, avx512dq, rdseed, adx, smap, avx512ifma, clflushopt, clwb, avx512cd, sha_ni, avx512bw, avx512vl, xsaveopt, xsavec, xgetbv1, xsaves, avx_vnni, avx512_bf16, clzero, xsaveerptr, wbnoinvd, arat, avx512vbmi, umip, pku, ospke, avx512_vbmi2, gfni, vaes, vpclmulqdq, avx512_vnni, avx512_bitalg, avx512_vpopcntdq, la57, rdpid, movdiri, movdir64b, avx512_vp2intersect, arch_capabilities
Ecpus
15.4
Scalability
96.25

System Resources and Accelerators

MEMORY
Memory Amount
128 GiB
Memory Amount Actual
128 GiB
GPU
GPU Count
0
GPU Memory Min
0 MiB
GPU Memory Total
0 MiB
GPUs
    STORAGE
    Storage Size
    0 GB
    Storages
      NETWORK
      Inbound Traffic
      0 GB/month
      Outbound Traffic
      35840 GB/month
      IPv4
      1

      CPU and System Topology

      Server Description

      A memory-optimized virtual server featuring sixteen shared AMD EPYC cores and high-capacity RAM for memory-intensive computing tasks.

      Memory OptimizedGeneral Purpose

      UpCloud CLOUDNATIVE-16xCPU-128GB is a memory-optimized virtual server running on the KVM hypervisor. It features 16 shared vCPUs powered by an AMD EPYC 9575F processor at 2.0 GHz, paired with 128.0 GB of RAM, yielding 8.0 GB of memory per core. The server does not include local storage or a GPU. In benchmark testing, it delivers top-tier single-core CPU performance and strong large-block memory read bandwidth, while multi-core and general computing metrics remain average. The shared CPU allocation presents a tradeoff for sustained multi-core workloads, but the high memory capacity makes it highly suitable for memory-intensive applications, database operations, caching, and single-threaded processing tasks.

      Economics

      Average Price per Region

      Prices per Zone

      Lowest Prices

      Performance

      Workload Profiles

      1.54Score
      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) 3,544,857 ops/sec 1,917,397 ops/sec 1.85 50.00% 50.00% +36.00%
      Redis RPS (pipeline=16, SET) 17,339,162 ops/sec 11,681,410 ops/sec 1.48 20.00% 20.00% +8.16%
      PassMark Memory Mark (composite) 1,996 2,418 0.825 10.00% 10.00% -1.91%
      Memory bandwidth (read, 16 MB ~ L3) 162,344 MB/sec 108,140 MB/sec 1.5 10.00% 10.00% +4.14%
      PassMark single-thread CPU 2,939 Mops/s 2,365 Mops/s 1.24 10.00% 10.00% +2.17%

      Memory Bandwidth

      Compression

      OpenSSL

      Geekbench Single-Core

      Score: 1,760

      Geekbench Multi-Core

      Score: 11,925

      Passmark CPU Scores

      BENCHMARKSCORE
      Mark
      35025
      Compression
      381245
      Encryption
      21076
      Extended Instructions
      32580
      Floating Point Maths
      98929
      Integer Maths
      103793
      Physics
      3621
      Prime Numbers
      207
      Single Threaded
      2939
      String Sorting
      49667

      Passmark Memory Scores

      BENCHMARKSCORE
      Memory Mark
      1996
      Database Operations
      11936
      Memory Latency
      120
      Memory Read Cached
      29144
      Memory Read Uncached
      19629
      Memory Write
      20884

      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

      PostgreSQL heavy read-only throughput

      Alternatives

      Similar Servers

      INSTANCEVENDORvCPUsMEMORYGPUs

      CLOUDNATIVE-16xCPU-128GB FAQs