vcg-a16-12c-128g-32vram by Vultr
(All-cores)
(Single-core)
Specifications
Server Metadata
Vendor ID | vultr |
Name | vcg-a16-12c-128g-32vram |
Description | Cloud GPU (12 vCPUs, 128.0 GiB RAM, 700 GB NVMe, 2xA16 16 GiB VRAM) |
Family | Cloud GPU |
Hw Virt | |
Average Time To Start | 107.67 |
Status | active |
Observed At | 2026-07-20T13:40:44.473138 |
Availability
| REGION / ID | SPOT | ONDEMAND |
|---|
Processor
vCPUs | 12 |
CPU Allocation | Shared |
CPU Cores | 6 |
CPU Speed | 2 GHz |
CPU Architecture | x86_64 |
CPU Manufacturer | Intel |
CPU L1D Cache | 32 KiB |
CPU L1D Cache Total | 384 KiB |
CPU L1I Cache | 32 KiB |
CPU L1I Cache Total | 384 KiB |
CPU L2 Cache | 4 MiB |
CPU L2 Cache Total | 24 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, rdtscp, lm, constant_tsc, rep_good, nopl, xtopology, 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, cpuid_fault, pti, ssbd, ibrs, ibpb, fsgsbase, bmi1, avx2, smep, bmi2, erms, invpcid, xsaveopt, arat |
Ecpus | 12 |
Scalability | 200 |
System Resources and Accelerators
| MEMORY | |
|---|---|
Memory Amount | 128 GiB |
Memory Amount Actual | 128 GiB |
| GPU | |
|---|---|
GPU Count | 2 |
GPU Memory Min | 16 GiB |
GPU Memory Total | 32 GiB |
GPU Manufacturer | NVIDIA |
GPU Family | Ampere |
GPU Model | A16 |
GPUs |
| STORAGE | |
|---|---|
Storage Size | 700 GB |
Storage Type | nvme ssd |
Storages |
| NETWORK | |
|---|---|
Inbound Traffic | 0 GB/month |
Outbound Traffic | 10240 GB/month |
IPv4 | 1 |
CPU and System Topology
Server Description
A dual-GPU accelerated server featuring high system memory density and NVMe storage for parallel processing and machine learning inference.
Vultr vcg-a16-12c-128g-32vram is a Cloud GPU server featuring 12 shared Intel x86_64 vCPUs, 128.0 GB of system memory, and a 700 GB NVMe SSD. It integrates two NVIDIA Ampere A16 GPUs with a total of 32 GB VRAM. Performance benchmarks indicate average multi-core CPU capabilities, with a stress-ng multi-core score of 21080.54 and a PassMark CPU score of 20085.48. However, its LLM inference capabilities are notable, achieving top-tier prompt processing speeds of 613.27 tokens/sec and strong text generation speeds of 32.35 tokens/sec on a medium 7B model. The shared CPU allocation represents a tradeoff for CPU-heavy tasks, but the high memory-to-core ratio of 10.67 GB and dual-GPU setup make it cost-efficient for memory-intensive parallel processing. This server is suited for medium-scale machine learning inference, data processing, and GPU-accelerated database workloads.
Economics
Performance
Memory Bandwidth
Compression
OpenSSL
Passmark CPU Scores
| BENCHMARK | SCORE |
|---|---|
Mark | 20085 |
Compression | 252141 |
Encryption | 7216 |
Extended Instructions | 17438 |
Floating Point Maths | 47566 |
Integer Maths | 59087 |
Physics | 2831 |
Prime Numbers | 186 |
Single Threaded | 2262 |
String Sorting | 34879 |
Passmark Memory Scores
| BENCHMARK | SCORE |
|---|---|
Memory Mark | 2234 |
Database Operations | 5284 |
Memory Latency | 69 |
Memory Read Cached | 22174 |
Memory Read Uncached | 11180 |
Memory Write | 8353 |
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
| INSTANCE | vCPUs | MEMORY | GPUs |
|---|---|---|---|
| vcg-a40-1c-5g-2vram | 1 | 5 GiB | 1⁄24 |
| vcg-a40-2c-10g-4vram | 2 | 10 GiB | 1⁄12 |
| vcg-a16-2c-8g-2vram | 2 | 8 GiB | ⅛ |
| vcg-a16-2c-16g-4vram | 2 | 16 GiB | ¼ |
| vcg-a16-3c-32g-8vram | 3 | 32 GiB | ½ |
| vcg-a40-4c-20g-8vram | 4 | 20 GiB | ⅙ |
| vcg-a40-6c-30g-12vram | 6 | 30 GiB | ¼ |
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