To be filled by O.E.M. CM1855
Geekbench ML Score
218
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows x86 (64-bit)
Result Information
| Upload Date | August 17 2024 06:43 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | To be filled by O.E.M. CM1855 |
| Motherboard | ASUSTeK COMPUTER INC. CM1855 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD FX-4300 |
| Topology | 1 Processor, 2 Cores, 4 Threads |
| Identifier | AuthenticAMD Family 21 Model 2 Stepping 0 |
| Base Frequency | 3.80 GHz |
| Cluster 1 | 2 Cores |
| L1 Instruction Cache | 64.0 KB x 2 |
| L1 Data Cache | 16.0 KB x 4 |
| L2 Cache | 2.00 MB x 2 |
| L3 Cache | 4.00 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% |
113
21.1 IPS |
|
|
Image Classification (F16)
|
100% |
111
20.8 IPS |
|
|
Image Classification (I8)
|
96% |
205
38.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
87
1.45 IPS |
|
|
Image Segmentation (F16)
|
100% |
88
1.47 IPS |
|
|
Image Segmentation (I8)
|
97% |
199
3.32 IPS |
|
|
Pose Estimation (F32)
|
100% |
231
0.28 IPS |
|
|
Pose Estimation (F16)
|
100% |
226
0.27 IPS |
|
|
Pose Estimation (I8)
|
100% |
437
0.53 IPS |
|
|
Object Detection (F32)
|
100% |
115
8.56 IPS |
|
|
Object Detection (F16)
|
100% |
116
8.66 IPS |
|
|
Object Detection (I8)
|
62% |
158
11.8 IPS |
|
|
Face Detection (F32)
|
100% |
253
3.01 IPS |
|
|
Face Detection (F16)
|
100% |
250
2.98 IPS |
|
|
Face Detection (I8)
|
87% |
417
4.96 IPS |
|
|
Depth Estimation (F32)
|
100% |
306
2.37 IPS |
|
|
Depth Estimation (F16)
|
100% |
305
2.37 IPS |
|
|
Depth Estimation (I8)
|
74% |
513
3.98 IPS |
|
|
Style Transfer (F32)
|
100% |
674
0.89 IPS |
|
|
Style Transfer (F16)
|
100% |
670
0.88 IPS |
|
|
Style Transfer (I8)
|
85% |
963
1.27 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
142
5.06 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
141
5.02 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
243
8.67 IPS |
|
|
Text Classification (F32)
|
100% |
154
221.2 IPS |
|
|
Text Classification (F16)
|
100% |
157
225.1 IPS |
|
|
Text Classification (I8)
|
94% |
114
163.9 IPS |
|
|
Machine Translation (F32)
|
100% |
228
4.20 IPS |
|
|
Machine Translation (F16)
|
100% |
229
4.22 IPS |
|
|
Machine Translation (I8)
|
67% |
202
3.71 IPS |
