Explore Hyperstack's A100_80G cloud instance specifications and benchmarks. Compare hardware configurations and performance metrics to optimize your AI and ML workloads.
LLM Benchmark Comparison
Hardware Specifications
GPU Configuration | Value |
---|---|
GPU Type | A100_80G |
GPU Interconnect | PCIE |
GPU Model Name | NVIDIA A100 80GB PCIe |
Driver Version | 535.154.05 |
GPU VRAM | 80 |
Power Limit (W) | 300.00 |
GPU Temperature (°C) | 44 |
GPU Clock Speed (MHz) | 210 |
Memory Clock Speed (MHz) | 1512 |
Pstate | P0 |
CPU Configuration | Value |
---|---|
Model Name | AMD EPYC 7763 64-Core Processor |
Vendor ID | AuthenticAMD |
CPUs | 28 |
CPU Clock Speed | 4890.81 |
Threads Per Core | 1 |
Cores Per Socket | 14 |
Sockets | 2 |
Memory | Value |
---|---|
Total | 118Gb |
Disks Specifications
Storage | Value |
---|---|
Total | 850.00GB |
Available Disks
Property | Value |
---|---|
Disk 1 | |
Model | vda |
Size | 100Gb |
Type | HDD |
Mount Point | Unmounted |
Disk 2 | |
Model | vdb |
Size | 750Gb |
Type | HDD |
Mount Point | /ephemeral |
Software Specifications
Software | Value |
---|---|
OS | Ubuntu |
OS Version | 22.04.3 LTS (Jammy Jellyfish) |
Cuda Driver | 12.2 |
Docker Version | 27.3.1 |
Python Version | Python 3.10.12 |
Benchmarks
Benchmark | Value |
---|---|
ffmpeg | 61 |
Coremark (Itterations per sec) | 31508.468 |
llama2Inference (Tokens per sec) | 50.22 |
Tensorflow Mnist Training | 2.278 |
Nvidia-smi output
Nvidia-smi topo -m outpu