ASUSTeK COMPUTER INC. ASUS Vivobook Pro 15 N6506CU_N6506CU
Geekbench ML Score
4112
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 05 2025 05:11 PM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | ASUSTeK COMPUTER INC. ASUS Vivobook Pro 15 N6506CU_N6506CU |
| Motherboard | ASUSTeK COMPUTER INC. N6506CU |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 9 285H |
| Topology | 1 Processor, 16 Cores |
| Identifier | GenuineIntel Family 6 Model 197 Stepping 2 |
| Base Frequency | 2.90 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| L1 Instruction Cache | 64.0 KB x 8 |
| L1 Data Cache | 48.0 KB x 8 |
| L2 Cache | 3.00 MB x 2 |
| L3 Cache | 24.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 24.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Arc(TM) 140T GPU (12GB) |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2948
551.6 IPS |
|
|
Image Classification (F16)
|
100% |
2868
536.7 IPS |
|
|
Image Classification (I8)
|
99% |
2299
430.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
2344
39.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
2422
40.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
1808
30.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
16764
20.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
16879
20.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
12945
15.7 IPS |
|
|
Object Detection (F32)
|
100% |
2703
201.8 IPS |
|
|
Object Detection (F16)
|
100% |
2715
202.7 IPS |
|
|
Object Detection (I8)
|
60% |
2177
162.6 IPS |
|
|
Face Detection (F32)
|
100% |
3600
42.8 IPS |
|
|
Face Detection (F16)
|
100% |
4004
47.6 IPS |
|
|
Face Detection (I8)
|
88% |
2633
31.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
11105
86.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
11752
91.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
8108
62.9 IPS |
|
|
Style Transfer (F32)
|
100% |
41399
54.5 IPS |
|
|
Style Transfer (F16)
|
100% |
39805
52.4 IPS |
|
|
Style Transfer (I8)
|
98% |
29828
39.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7152
255.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
7225
258.0 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
4242
151.5 IPS |
|
|
Text Classification (F32)
|
90% |
690
991.8 IPS |
|
|
Text Classification (F16)
|
90% |
675
970.7 IPS |
|
|
Text Classification (I8)
|
90% |
511
735.1 IPS |
|
|
Machine Translation (F32)
|
100% |
1531
28.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1558
28.7 IPS |
|
|
Machine Translation (I8)
|
70% |
923
17.0 IPS |
