ASUS System Product Name
Geekbench AI Score
42334
Single Precision Score
62170
Half Precision Score
31417
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | alexb |
| Upload Date | July 03 2025 07:30 AM |
| Views | 6 |
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% |
15321
2.85 KIPS |
|
|
Image Classification (HP)
|
100% |
20044
3.73 KIPS |
|
|
Image Classification (Q)
|
100% |
12991
2.42 KIPS |
|
|
Image Segmentation (SP)
|
100% |
30470
493.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
36909
598.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
27834
452.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
377161
440.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
841131
981.5 IPS |
|
|
Pose Estimation (Q)
|
96% |
304548
356.7 IPS |
|
|
Object Detection (SP)
|
100% |
20778
1.65 KIPS |
|
|
Object Detection (HP)
|
100% |
26487
2.10 KIPS |
|
|
Object Detection (Q)
|
85% |
17626
1.42 KIPS |
|
|
Face Detection (SP)
|
100% |
60534
719.3 IPS |
|
|
Face Detection (HP)
|
100% |
76401
907.8 IPS |
|
|
Face Detection (Q)
|
97% |
49368
588.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
97916
754.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
177748
1.37 KIPS |
|
|
Depth Estimation (Q)
|
77% |
70230
562.5 IPS |
|
|
Style Transfer (SP)
|
100% |
552156
709.8 IPS |
|
|
Style Transfer (HP)
|
100% |
1474690
1.90 KIPS |
|
|
Style Transfer (Q)
|
98% |
464946
599.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
65106
2.40 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
88518
3.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
46742
1.73 KIPS |
|
|
Text Classification (SP)
|
100% |
3844
5.13 KIPS |
|
|
Text Classification (HP)
|
100% |
4761
6.35 KIPS |
|
|
Text Classification (Q)
|
97% |
2213
2.96 KIPS |
|
|
Machine Translation (SP)
|
100% |
6170
106.3 IPS |
|
|
Machine Translation (HP)
|
100% |
6201
106.8 IPS |
|
|
Machine Translation (Q)
|
70% |
2895
54.3 IPS |
