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GPU-8xCPU-64GB-1xL4 by UpCloud

GPU-8xCPU-64GB-1xL4 is a GPU (8 vCPUs, 64 GiB RAM, 1x L4) server offered by UpCloud with 8 vCPUs, 64 GiB of memory and 0 GB of storage. The pricing starts at 0.6492 USD per hour.
8 vCPU
64 GiB Memory
1 GPU
Spare SCore
32452
(All-cores)
4093
(Single-core)

Specifications

Server Metadata

Vendor ID
upcloud
Name
GPU-8xCPU-64GB-1xL4
Description
GPU (8 vCPUs, 64 GiB RAM, 1x L4)
Family
GPU
Hw Virt
Average Time To Start
74
Status
active
Observed At
2026-07-27T21:49:11.491643

Availability

REGION / IDSPOTONDEMAND
Helsinki #2 (FI) / fi-hel2
0.6492 USD/h 0.661 USD/h

Processor

vCPUs
8
Hypervisor
KVM
CPU Allocation
Shared
CPU Cores
8
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
512 KiB
CPU L1I Cache
64 KiB
CPU L1I Cache Total
512 KiB
CPU L2 Cache
512 KiB
CPU L2 Cache Total
4 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
7.9
Scalability
98.75

System Resources and Accelerators

MEMORY
Memory Amount
64 GiB
Memory Amount Actual
64 GiB
GPU
GPU Count
1
GPU Memory Min
24 GiB
GPU Memory Total
24 GiB
GPU Manufacturer
NVIDIA
GPU Family
Ada Lovelace
GPU Model
L4
GPUs
    STORAGE
    Storage Size
    0 GB
    Storages
      NETWORK
      Inbound Traffic
      0 GB/month
      Outbound Traffic
      16384 GB/month
      IPv4
      1

      CPU and System Topology

      Server Description

      A GPU-accelerated virtual server combining shared AMD EPYC processors with an NVIDIA L4 GPU for efficient machine learning inference.

      GPU AcceleratedMemory Optimized

      UpCloud GPU-8xCPU-64GB-1xL4 is a GPU-accelerated virtual server running on the KVM hypervisor. It features an AMD EPYC 9575F processor with 8 shared vCPUs, 8 physical cores, and 64.0 GB of system memory. Graphics and compute acceleration are delivered via a single NVIDIA L4 GPU with 24 GB of VRAM based on the Ada Lovelace architecture. The server does not include local storage. In benchmark testing, the instance demonstrates top-tier single-core CPU performance and high-speed text generation for small LLM models, alongside average multi-core and memory bandwidth capabilities. This hardware configuration offers a cost-effective profile for GPU-reliant tasks by utilizing shared CPU resources. It is highly suited for machine learning inference, data science, and single-threaded processing workloads that connect to remote storage.

      Economics

      Average Price per Region

      Prices per Zone

      Lowest Prices

      Performance

      Workload Profiles

      1.59Score
      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) 2,811,324 ops/sec 1,896,415 ops/sec 1.48 50.00% 50.00% +21.70%
      Redis RPS (pipeline=16, SET) 17,944,116 ops/sec 11,539,523 ops/sec 1.56 20.00% 20.00% +9.30%
      PassMark Memory Mark (composite) 2,726 2,411 1.13 10.00% 10.00% +1.23%
      Memory bandwidth (read, 16 MB ~ L3) 318,893 MB/sec 107,368 MB/sec 2.97 10.00% 10.00% +11.50%
      PassMark single-thread CPU 4,070 Mops/s 2,363 Mops/s 1.72 10.00% 10.00% +5.57%

      Memory Bandwidth

      Compression

      OpenSSL

      Passmark CPU Scores

      BENCHMARKSCORE
      Mark
      27004
      Compression
      279090
      Encryption
      13817
      Extended Instructions
      23845
      Floating Point Maths
      66174
      Integer Maths
      62345
      Physics
      3978
      Prime Numbers
      238
      Single Threaded
      4070
      String Sorting
      37550

      Passmark Memory Scores

      BENCHMARKSCORE
      Memory Mark
      2726
      Database Operations
      10495
      Memory Latency
      87
      Memory Read Cached
      36992
      Memory Read Uncached
      33881
      Memory Write
      33230

      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
      GPU-8xCPU-64GB-1xL40S 864 GiB1
      GPU-12xCPU-128GB-1xL4 12128 GiB1
      GPU-12xCPU-128GB-1xL40S 12128 GiB1
      GPU-12xCPU-240GB-1xH100 12240 GiB1
      GPU-12xCPU-128GB-2xL4 12128 GiB2
      GPU-12xCPU-128GB-2xL40S 12128 GiB2
      GPU-16xCPU-192GB-1xL4 16192 GiB1

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      GPU-8xCPU-64GB-1xL4 FAQs