Inspur NF5568M4
Geekbench AI Score
10707
Single Precision Score
16139
Half Precision Score
7625
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | zeallag |
| Upload Date | February 21 2025 06:20 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA Tesla T10 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows Server 2022 Datacenter (64-bit) |
| Model | Inspur NF5568M4 |
| Motherboard | Inspur NF5568M4 |
| CPU Information | |
|---|---|
| Name | Intel Xeon E5-2680 v4 |
| Topology | 2 Processors, 28 Cores, 56 Threads |
| Identifier | GenuineIntel Family 6 Model 79 Stepping 1 |
| Base Frequency | 2.40 GHz |
| Cluster 1 | 28 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
4468
831.0 IPS |
|
|
Image Classification (HP)
|
100% |
6020
1.12 KIPS |
|
|
Image Classification (Q)
|
99% |
3540
660.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
6555
106.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
7751
125.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
5289
86.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
71617
83.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
174301
203.4 IPS |
|
|
Pose Estimation (Q)
|
96% |
55522
65.1 IPS |
|
|
Object Detection (SP)
|
100% |
5459
433.0 IPS |
|
|
Object Detection (HP)
|
100% |
7947
630.4 IPS |
|
|
Object Detection (Q)
|
84% |
4295
346.4 IPS |
|
|
Face Detection (SP)
|
100% |
12781
151.9 IPS |
|
|
Face Detection (HP)
|
100% |
18780
223.1 IPS |
|
|
Face Detection (Q)
|
97% |
9865
117.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
30501
235.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
51253
394.9 IPS |
|
|
Depth Estimation (Q)
|
77% |
20484
164.1 IPS |
|
|
Style Transfer (SP)
|
100% |
130761
168.1 IPS |
|
|
Style Transfer (HP)
|
100% |
282598
363.3 IPS |
|
|
Style Transfer (Q)
|
98% |
96615
124.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
18609
687.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
23504
867.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
11519
426.5 IPS |
|
|
Text Classification (SP)
|
100% |
848
1.13 KIPS |
|
|
Text Classification (HP)
|
99% |
1342
1.79 KIPS |
|
|
Text Classification (Q)
|
97% |
635
850.1 IPS |
|
|
Machine Translation (SP)
|
100% |
2151
37.1 IPS |
|
|
Machine Translation (HP)
|
100% |
2162
37.2 IPS |
|
|
Machine Translation (Q)
|
70% |
1042
19.5 IPS |
