ASUS System Product Name
Geekbench AI Score
35822
Single Precision Score
52313
Half Precision Score
27310
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | B007Cyber |
| Upload Date | August 10 2025 12:01 PM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4080 SUPER |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | ASUS System Product Name |
| Motherboard | ASUSTeK COMPUTER INC. ROG MAXIMUS Z690 HERO EVA |
| Power Plan | Balanced |
| 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 | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
13256
2.47 KIPS |
|
|
Image Classification (HP)
|
99% |
18441
3.44 KIPS |
|
|
Image Classification (Q)
|
100% |
11548
2.15 KIPS |
|
|
Image Segmentation (SP)
|
100% |
24697
400.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
32343
524.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
22396
364.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
273408
319.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
516066
602.2 IPS |
|
|
Pose Estimation (Q)
|
96% |
234825
275.1 IPS |
|
|
Object Detection (SP)
|
100% |
17665
1.40 KIPS |
|
|
Object Detection (HP)
|
100% |
24579
1.95 KIPS |
|
|
Object Detection (Q)
|
85% |
15052
1.21 KIPS |
|
|
Face Detection (SP)
|
100% |
51153
607.8 IPS |
|
|
Face Detection (HP)
|
100% |
66940
795.4 IPS |
|
|
Face Detection (Q)
|
97% |
43442
518.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
85048
655.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
155814
1.20 KIPS |
|
|
Depth Estimation (Q)
|
78% |
65820
525.6 IPS |
|
|
Style Transfer (SP)
|
100% |
396501
509.7 IPS |
|
|
Style Transfer (HP)
|
100% |
932129
1.20 KIPS |
|
|
Style Transfer (Q)
|
98% |
355552
458.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
57095
2.11 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
76899
2.84 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
43107
1.60 KIPS |
|
|
Text Classification (SP)
|
100% |
3694
4.93 KIPS |
|
|
Text Classification (HP)
|
99% |
4520
6.03 KIPS |
|
|
Text Classification (Q)
|
97% |
2211
2.96 KIPS |
|
|
Machine Translation (SP)
|
100% |
6050
104.2 IPS |
|
|
Machine Translation (HP)
|
100% |
6005
103.4 IPS |
|
|
Machine Translation (Q)
|
70% |
2606
48.9 IPS |
