SchenkerTechnologiesGmbH XMG APEX (Mid 2021)
Geekbench ML Score
2923
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| User | chaton22 |
| Upload Date | August 15 2024 04:35 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Professionnel (64-bit) |
| Model | SchenkerTechnologiesGmbH XMG APEX (Mid 2021) |
| Motherboard | NB01 NHx0ERQ_EPS |
| Power Plan | Utilisation normale |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 5900HX |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 80 Stepping 0 |
| Base Frequency | 3.30 GHz |
| Cluster 1 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 8 |
| L1 Data Cache | 32.0 KB x 8 |
| L2 Cache | 512 KB x 8 |
| L3 Cache | 16.0 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% |
1560
291.9 IPS |
|
|
Image Classification (F16)
|
100% |
1598
299.1 IPS |
|
|
Image Classification (I8)
|
97% |
3178
594.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
1140
19.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1122
18.7 IPS |
|
|
Image Segmentation (I8)
|
97% |
2356
39.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
5166
6.26 IPS |
|
|
Pose Estimation (F16)
|
100% |
5205
6.30 IPS |
|
|
Pose Estimation (I8)
|
100% |
11518
13.9 IPS |
|
|
Object Detection (F32)
|
100% |
1663
124.1 IPS |
|
|
Object Detection (F16)
|
100% |
1651
123.3 IPS |
|
|
Object Detection (I8)
|
60% |
1601
119.5 IPS |
|
|
Face Detection (F32)
|
100% |
1879
22.3 IPS |
|
|
Face Detection (F16)
|
100% |
1859
22.1 IPS |
|
|
Face Detection (I8)
|
87% |
3285
39.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
5281
41.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
6209
48.2 IPS |
|
|
Depth Estimation (I8)
|
74% |
9967
77.3 IPS |
|
|
Style Transfer (F32)
|
100% |
12683
16.7 IPS |
|
|
Style Transfer (F16)
|
100% |
12338
16.2 IPS |
|
|
Style Transfer (I8)
|
85% |
13274
17.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2277
81.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2267
81.0 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
2796
99.9 IPS |
|
|
Text Classification (F32)
|
100% |
1549
2.23 KIPS |
|
|
Text Classification (F16)
|
100% |
1634
2.35 KIPS |
|
|
Text Classification (I8)
|
94% |
1239
1.78 KIPS |
|
|
Machine Translation (F32)
|
100% |
1826
33.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1868
34.4 IPS |
|
|
Machine Translation (I8)
|
67% |
2417
44.5 IPS |
