GEEKOM A8
Geekbench ML Score
3725
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | July 06 2024 09:17 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | GEEKOM A8 |
| Motherboard | Default string A8 |
| Power Plan | Ausbalanciert |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 8945HS |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 117 Stepping 2 |
| Base Frequency | 4.00 GHz |
| Cluster 1 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 8 |
| L1 Data Cache | 32.0 KB x 8 |
| L2 Cache | 1.00 MB x 8 |
| L3 Cache | 16.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2135
399.6 IPS |
|
|
Image Classification (F16)
|
100% |
2118
396.4 IPS |
|
|
Image Classification (I8)
|
99% |
5115
957.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
1024
17.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
911
15.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
2505
41.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
7329
8.88 IPS |
|
|
Pose Estimation (F16)
|
100% |
6648
8.05 IPS |
|
|
Pose Estimation (I8)
|
100% |
26174
31.7 IPS |
|
|
Object Detection (F32)
|
100% |
2098
156.6 IPS |
|
|
Object Detection (F16)
|
100% |
2046
152.8 IPS |
|
|
Object Detection (I8)
|
62% |
2036
152.0 IPS |
|
|
Face Detection (F32)
|
100% |
3575
42.5 IPS |
|
|
Face Detection (F16)
|
100% |
3609
42.9 IPS |
|
|
Face Detection (I8)
|
89% |
5477
65.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
8452
65.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
8167
63.3 IPS |
|
|
Depth Estimation (I8)
|
96% |
15545
120.5 IPS |
|
|
Style Transfer (F32)
|
100% |
15771
20.7 IPS |
|
|
Style Transfer (F16)
|
100% |
13608
17.9 IPS |
|
|
Style Transfer (I8)
|
98% |
25388
33.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2867
102.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2450
87.5 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
3687
131.7 IPS |
|
|
Text Classification (F32)
|
100% |
2052
2.95 KIPS |
|
|
Text Classification (F16)
|
100% |
2037
2.93 KIPS |
|
|
Text Classification (I8)
|
98% |
374
537.1 IPS |
|
|
Machine Translation (F32)
|
100% |
2245
41.3 IPS |
|
|
Machine Translation (F16)
|
100% |
2197
40.4 IPS |
|
|
Machine Translation (I8)
|
67% |
2746
50.5 IPS |
