ASUSTeK COMPUTER INC. ASUS Vivobook Pro 15 N6506CU_N6506CU
Geekbench ML Score
4068
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 05 2025 05:10 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% |
2964
554.6 IPS |
|
|
Image Classification (F16)
|
100% |
2913
545.1 IPS |
|
|
Image Classification (I8)
|
99% |
2213
414.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
2371
39.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
2367
39.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
1760
29.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
17086
20.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
16787
20.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
13033
15.8 IPS |
|
|
Object Detection (F32)
|
100% |
2445
182.5 IPS |
|
|
Object Detection (F16)
|
100% |
2580
192.6 IPS |
|
|
Object Detection (I8)
|
60% |
2134
159.3 IPS |
|
|
Face Detection (F32)
|
100% |
3640
43.3 IPS |
|
|
Face Detection (F16)
|
100% |
3988
47.4 IPS |
|
|
Face Detection (I8)
|
88% |
2672
31.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
10866
84.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
11385
88.3 IPS |
|
|
Depth Estimation (I8)
|
95% |
8238
63.9 IPS |
|
|
Style Transfer (F32)
|
100% |
41355
54.4 IPS |
|
|
Style Transfer (F16)
|
100% |
41040
54.0 IPS |
|
|
Style Transfer (I8)
|
98% |
29505
38.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6563
234.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
6741
240.7 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
4106
146.7 IPS |
|
|
Text Classification (F32)
|
90% |
700
1.01 KIPS |
|
|
Text Classification (F16)
|
90% |
705
1.01 KIPS |
|
|
Text Classification (I8)
|
90% |
525
755.1 IPS |
|
|
Machine Translation (F32)
|
100% |
1549
28.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1548
28.5 IPS |
|
|
Machine Translation (I8)
|
70% |
907
16.7 IPS |
