ASUS System Product Name
Geekbench AI Score
38399
Single Precision Score
53289
Half Precision Score
28744
Quantized Score
Geekbench AI 1.0.0 for Windows AVX2
Result Information
| User | lautajo |
| Upload Date | August 16 2024 12:03 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4090 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | ASUS System Product Name |
| Motherboard | ASUSTeK COMPUTER INC. ROG MAXIMUS Z790 APEX |
| Power Plan | Paras suoritusteho |
| CPU Information | |
|---|---|
| Name | Intel Core i9-13900K |
| Topology | 1 Processor, 24 Cores, 32 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.00 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
14628
2.72 KIPS |
|
|
Image Classification (HP)
|
99% |
19534
3.64 KIPS |
|
|
Image Classification (Q)
|
100% |
12234
2.28 KIPS |
|
|
Image Segmentation (SP)
|
100% |
22897
371.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
27951
453.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
20936
340.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
302944
353.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
551369
643.4 IPS |
|
|
Pose Estimation (Q)
|
97% |
264510
309.7 IPS |
|
|
Object Detection (SP)
|
100% |
19015
1.51 KIPS |
|
|
Object Detection (HP)
|
100% |
25107
1.99 KIPS |
|
|
Object Detection (Q)
|
89% |
16267
1.30 KIPS |
|
|
Face Detection (SP)
|
100% |
50693
602.3 IPS |
|
|
Face Detection (HP)
|
100% |
61772
734.0 IPS |
|
|
Face Detection (Q)
|
97% |
42267
504.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
97133
748.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
166666
1.28 KIPS |
|
|
Depth Estimation (Q)
|
75% |
70669
570.5 IPS |
|
|
Style Transfer (SP)
|
100% |
561773
722.2 IPS |
|
|
Style Transfer (HP)
|
100% |
1101886
1.42 KIPS |
|
|
Style Transfer (Q)
|
98% |
482354
622.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
62966
2.33 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
84546
3.12 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
46133
1.71 KIPS |
|
|
Text Classification (SP)
|
100% |
4048
5.40 KIPS |
|
|
Text Classification (HP)
|
99% |
5065
6.76 KIPS |
|
|
Text Classification (Q)
|
97% |
2385
3.19 KIPS |
|
|
Machine Translation (SP)
|
100% |
5124
88.3 IPS |
|
|
Machine Translation (HP)
|
100% |
5030
86.7 IPS |
|
|
Machine Translation (Q)
|
60% |
2204
49.2 IPS |
