Supermicro Super Server
Geekbench AI Score
3884
Single Precision Score
1418
Half Precision Score
4985
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| Upload Date | September 22 2025 05:05 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | AMD EPYC 7343 |
| System Information | |
|---|---|
| Operating System | Windows 10 Pro (64-bit) |
| Model | Supermicro Super Server |
| Motherboard | Supermicro H12SSL-i |
| CPU Information | |
|---|---|
| Name | AMD EPYC 7343 |
| Topology | 1 Processor, 16 Cores, 32 Threads |
| Identifier | AuthenticAMD Family 25 Model 1 Stepping 1 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 256.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
3127
581.4 IPS |
|
|
Image Classification (HP)
|
100% |
447
83.2 IPS |
|
|
Image Classification (Q)
|
96% |
4753
887.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1758
28.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
700
11.3 IPS |
|
|
Image Segmentation (Q)
|
97% |
5325
86.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
10103
11.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
6790
7.92 IPS |
|
|
Pose Estimation (Q)
|
86% |
18602
22.0 IPS |
|
|
Object Detection (SP)
|
100% |
3370
267.3 IPS |
|
|
Object Detection (HP)
|
100% |
621
49.2 IPS |
|
|
Object Detection (Q)
|
58% |
3582
391.3 IPS |
|
|
Face Detection (SP)
|
100% |
7712
91.6 IPS |
|
|
Face Detection (HP)
|
100% |
1250
14.8 IPS |
|
|
Face Detection (Q)
|
96% |
7841
93.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
10427
80.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
2266
17.5 IPS |
|
|
Depth Estimation (Q)
|
78% |
13200
105.3 IPS |
|
|
Style Transfer (SP)
|
100% |
20153
25.9 IPS |
|
|
Style Transfer (HP)
|
100% |
16427
21.1 IPS |
|
|
Style Transfer (Q)
|
87% |
28596
37.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1752
64.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1517
56.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2854
105.8 IPS |
|
|
Text Classification (SP)
|
100% |
1040
1.39 KIPS |
|
|
Text Classification (HP)
|
100% |
462
616.0 IPS |
|
|
Text Classification (Q)
|
97% |
342
458.5 IPS |
|
|
Machine Translation (SP)
|
100% |
1416
24.4 IPS |
|
|
Machine Translation (HP)
|
100% |
769
13.2 IPS |
|
|
Machine Translation (Q)
|
68% |
1946
37.6 IPS |
