ASUS System Product Name
Geekbench ML Score
2545
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | September 16 2024 12:36 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | ASUS System Product Name |
| Motherboard | ASUSTeK COMPUTER INC. PRIME Z590-P |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i9-10900K |
| Topology | 1 Processor, 10 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 165 Stepping 5 |
| Base Frequency | 3.70 GHz |
| Cluster 1 | 10 Cores |
| L1 Instruction Cache | 32.0 KB x 10 |
| L1 Data Cache | 32.0 KB x 10 |
| L2 Cache | 256 KB x 10 |
| L3 Cache | 20.0 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% |
1908
357.0 IPS |
|
|
Image Classification (F16)
|
100% |
1884
352.5 IPS |
|
|
Image Classification (I8)
|
97% |
2991
559.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
1496
25.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1575
26.3 IPS |
|
|
Image Segmentation (I8)
|
97% |
2038
34.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
7400
8.96 IPS |
|
|
Pose Estimation (F16)
|
100% |
7375
8.93 IPS |
|
|
Pose Estimation (I8)
|
100% |
14636
17.7 IPS |
|
|
Object Detection (F32)
|
100% |
1743
130.1 IPS |
|
|
Object Detection (F16)
|
100% |
1757
131.2 IPS |
|
|
Object Detection (I8)
|
60% |
1443
107.7 IPS |
|
|
Face Detection (F32)
|
100% |
1655
19.7 IPS |
|
|
Face Detection (F16)
|
100% |
1671
19.9 IPS |
|
|
Face Detection (I8)
|
87% |
2146
25.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
3444
26.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
4142
32.1 IPS |
|
|
Depth Estimation (I8)
|
74% |
6939
53.8 IPS |
|
|
Style Transfer (F32)
|
100% |
12030
15.8 IPS |
|
|
Style Transfer (F16)
|
100% |
12314
16.2 IPS |
|
|
Style Transfer (I8)
|
85% |
12516
16.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2094
74.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2609
93.2 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
2032
72.6 IPS |
|
|
Text Classification (F32)
|
100% |
1090
1.57 KIPS |
|
|
Text Classification (F16)
|
100% |
1186
1.70 KIPS |
|
|
Text Classification (I8)
|
94% |
315
452.3 IPS |
|
|
Machine Translation (F32)
|
100% |
1134
20.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1094
20.1 IPS |
|
|
Machine Translation (I8)
|
67% |
1344
24.7 IPS |
