To be filled by O.E.M. To be filled by O.E.M.
Geekbench ML Score
1337
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows x86 (64-bit)
Result Information
| Upload Date | August 17 2024 05:27 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | To be filled by O.E.M. To be filled by O.E.M. |
| Motherboard | INTEL X79F |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Xeon E5-2697 v2 |
| Topology | 1 Processor, 12 Cores |
| Identifier | GenuineIntel Family 6 Model 62 Stepping 4 |
| Base Frequency | 2.70 GHz |
| Cluster 1 | 12 Cores |
| L1 Instruction Cache | 32.0 KB x 6 |
| L1 Data Cache | 32.0 KB x 6 |
| L2 Cache | 256 KB x 6 |
| L3 Cache | 30.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
992
185.6 IPS |
|
|
Image Classification (F16)
|
100% |
977
182.8 IPS |
|
|
Image Classification (I8)
|
96% |
1010
188.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
800
13.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
810
13.5 IPS |
|
|
Image Segmentation (I8)
|
97% |
750
12.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
3044
3.69 IPS |
|
|
Pose Estimation (F16)
|
100% |
2679
3.24 IPS |
|
|
Pose Estimation (I8)
|
100% |
2834
3.43 IPS |
|
|
Object Detection (F32)
|
100% |
806
60.1 IPS |
|
|
Object Detection (F16)
|
100% |
776
57.9 IPS |
|
|
Object Detection (I8)
|
62% |
675
50.4 IPS |
|
|
Face Detection (F32)
|
100% |
1158
13.8 IPS |
|
|
Face Detection (F16)
|
100% |
1144
13.6 IPS |
|
|
Face Detection (I8)
|
87% |
1248
14.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
3442
26.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
3455
26.8 IPS |
|
|
Depth Estimation (I8)
|
74% |
2734
21.2 IPS |
|
|
Style Transfer (F32)
|
100% |
7224
9.50 IPS |
|
|
Style Transfer (F16)
|
100% |
7492
9.86 IPS |
|
|
Style Transfer (I8)
|
85% |
4611
6.07 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1530
54.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1525
54.4 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
1050
37.5 IPS |
|
|
Text Classification (F32)
|
100% |
667
958.7 IPS |
|
|
Text Classification (F16)
|
100% |
669
961.2 IPS |
|
|
Text Classification (I8)
|
94% |
231
332.3 IPS |
|
|
Machine Translation (F32)
|
100% |
829
15.3 IPS |
|
|
Machine Translation (F16)
|
100% |
801
14.7 IPS |
|
|
Machine Translation (I8)
|
67% |
594
10.9 IPS |
