ASUS System Product Name
Geekbench ML Score
3306
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | September 16 2024 07:06 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% |
2048
383.3 IPS |
|
|
Image Classification (F16)
|
100% |
2017
377.4 IPS |
|
|
Image Classification (I8)
|
97% |
3188
596.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
1679
28.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1699
28.4 IPS |
|
|
Image Segmentation (I8)
|
97% |
2026
33.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
7175
8.69 IPS |
|
|
Pose Estimation (F16)
|
100% |
6024
7.29 IPS |
|
|
Pose Estimation (I8)
|
100% |
13246
16.0 IPS |
|
|
Object Detection (F32)
|
100% |
1822
136.0 IPS |
|
|
Object Detection (F16)
|
100% |
1790
133.6 IPS |
|
|
Object Detection (I8)
|
60% |
1692
126.3 IPS |
|
|
Face Detection (F32)
|
100% |
1926
22.9 IPS |
|
|
Face Detection (F16)
|
100% |
2062
24.5 IPS |
|
|
Face Detection (I8)
|
87% |
3414
40.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
7429
57.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
7471
57.9 IPS |
|
|
Depth Estimation (I8)
|
74% |
11223
87.0 IPS |
|
|
Style Transfer (F32)
|
100% |
17363
22.8 IPS |
|
|
Style Transfer (F16)
|
100% |
17110
22.5 IPS |
|
|
Style Transfer (I8)
|
85% |
14498
19.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3387
120.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
3454
123.4 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
3603
128.7 IPS |
|
|
Text Classification (F32)
|
100% |
1554
2.23 KIPS |
|
|
Text Classification (F16)
|
100% |
1628
2.34 KIPS |
|
|
Text Classification (I8)
|
94% |
422
606.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1976
36.4 IPS |
|
|
Machine Translation (F16)
|
100% |
2003
36.9 IPS |
|
|
Machine Translation (I8)
|
67% |
2450
45.1 IPS |
