ASUS System Product Name
Geekbench AI Score
43278
Single Precision Score
63172
Half Precision Score
31843
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | alexb |
| Upload Date | July 06 2025 06:03 AM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5090 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | ASUS System Product Name |
| Motherboard | ASUSTeK COMPUTER INC. ROG STRIX Z890-I GAMING WIFI |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 9 285K |
| Topology | 1 Processor, 24 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 3.70 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 96.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
15546
2.89 KIPS |
|
|
Image Classification (HP)
|
100% |
20006
3.72 KIPS |
|
|
Image Classification (Q)
|
100% |
13129
2.44 KIPS |
|
|
Image Segmentation (SP)
|
100% |
31344
508.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
38125
618.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
29144
473.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
377945
441.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
844122
984.9 IPS |
|
|
Pose Estimation (Q)
|
96% |
306943
359.5 IPS |
|
|
Object Detection (SP)
|
100% |
21292
1.69 KIPS |
|
|
Object Detection (HP)
|
100% |
26957
2.14 KIPS |
|
|
Object Detection (Q)
|
85% |
17830
1.44 KIPS |
|
|
Face Detection (SP)
|
100% |
61312
728.5 IPS |
|
|
Face Detection (HP)
|
100% |
78240
929.7 IPS |
|
|
Face Detection (Q)
|
97% |
49401
589.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
98727
760.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
176235
1.36 KIPS |
|
|
Depth Estimation (Q)
|
77% |
70554
565.1 IPS |
|
|
Style Transfer (SP)
|
100% |
549880
706.9 IPS |
|
|
Style Transfer (HP)
|
100% |
1463399
1.88 KIPS |
|
|
Style Transfer (Q)
|
98% |
467849
603.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
65788
2.43 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
90442
3.34 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
46871
1.74 KIPS |
|
|
Text Classification (SP)
|
100% |
4111
5.49 KIPS |
|
|
Text Classification (HP)
|
100% |
4930
6.58 KIPS |
|
|
Text Classification (Q)
|
97% |
2253
3.02 KIPS |
|
|
Machine Translation (SP)
|
100% |
6530
112.5 IPS |
|
|
Machine Translation (HP)
|
100% |
6482
111.7 IPS |
|
|
Machine Translation (Q)
|
70% |
2973
55.8 IPS |
