ASUS System Product Name
Geekbench AI Score
31347
Single Precision Score
44943
Half Precision Score
24625
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | ageva |
| Upload Date | February 06 2025 09:11 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4080 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | ASUS System Product Name |
| Motherboard | ASUSTeK COMPUTER INC. ROG MAXIMUS Z790 HERO |
| Power Plan | Ultimate Performance |
| CPU Information | |
|---|---|
| Name | Intel Core i9-12900K |
| Topology | 1 Processor, 16 Cores, 24 Threads |
| Identifier | GenuineIntel Family 6 Model 151 Stepping 2 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
11914
2.22 KIPS |
|
|
Image Classification (HP)
|
99% |
17056
3.18 KIPS |
|
|
Image Classification (Q)
|
100% |
10343
1.92 KIPS |
|
|
Image Segmentation (SP)
|
100% |
18445
299.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
22651
367.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
16969
275.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
252776
294.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
476965
556.5 IPS |
|
|
Pose Estimation (Q)
|
96% |
224433
263.0 IPS |
|
|
Object Detection (SP)
|
100% |
14787
1.17 KIPS |
|
|
Object Detection (HP)
|
100% |
20909
1.66 KIPS |
|
|
Object Detection (Q)
|
85% |
12832
1.03 KIPS |
|
|
Face Detection (SP)
|
100% |
41953
498.5 IPS |
|
|
Face Detection (HP)
|
100% |
51352
610.2 IPS |
|
|
Face Detection (Q)
|
97% |
36098
430.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
79581
613.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
140237
1.08 KIPS |
|
|
Depth Estimation (Q)
|
78% |
62516
499.2 IPS |
|
|
Style Transfer (SP)
|
100% |
379372
487.7 IPS |
|
|
Style Transfer (HP)
|
100% |
802512
1.03 KIPS |
|
|
Style Transfer (Q)
|
98% |
332665
429.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
49949
1.84 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
69977
2.58 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
38754
1.44 KIPS |
|
|
Text Classification (SP)
|
100% |
3694
4.93 KIPS |
|
|
Text Classification (HP)
|
99% |
4546
6.07 KIPS |
|
|
Text Classification (Q)
|
97% |
2242
3.00 KIPS |
|
|
Machine Translation (SP)
|
100% |
4774
82.2 IPS |
|
|
Machine Translation (HP)
|
100% |
4747
81.8 IPS |
|
|
Machine Translation (Q)
|
70% |
2487
46.7 IPS |
