ASUSTeK COMPUTER INC. ROG Flow X16 GV601VV_GV601VV
Geekbench AI Score
2765
Single Precision Score
2770
Half Precision Score
1663
Quantized Score
Geekbench AI 1.0.0 for Windows AVX2
Result Information
| User | Foxyz |
| Upload Date | December 06 2024 09:10 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Iris(R) Xe Graphics |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Enterprise (64-bit) |
| Model | ASUSTeK COMPUTER INC. ROG Flow X16 GV601VV_GV601VV |
| Motherboard | ASUSTeK COMPUTER INC. GV601VV |
| Power Plan | Gebalanceerd |
| CPU Information | |
|---|---|
| Name | Intel Core i9-13900H |
| Topology | 1 Processor, 14 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 186 Stepping 2 |
| Base Frequency | 2.60 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1142
212.3 IPS |
|
|
Image Classification (HP)
|
100% |
1239
230.4 IPS |
|
|
Image Classification (Q)
|
100% |
864
160.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1720
27.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2132
34.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
1340
21.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
10860
12.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
11454
13.4 IPS |
|
|
Pose Estimation (Q)
|
96% |
5457
6.39 IPS |
|
|
Object Detection (SP)
|
100% |
1359
107.8 IPS |
|
|
Object Detection (HP)
|
98% |
1220
97.1 IPS |
|
|
Object Detection (Q)
|
89% |
1114
89.2 IPS |
|
|
Face Detection (SP)
|
100% |
2583
30.7 IPS |
|
|
Face Detection (HP)
|
100% |
3010
35.8 IPS |
|
|
Face Detection (Q)
|
97% |
1696
20.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
5392
41.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
6053
46.8 IPS |
|
|
Depth Estimation (Q)
|
73% |
3622
29.6 IPS |
|
|
Style Transfer (SP)
|
100% |
23333
30.0 IPS |
|
|
Style Transfer (HP)
|
100% |
30015
38.6 IPS |
|
|
Style Transfer (Q)
|
98% |
14875
19.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3143
116.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4211
155.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1341
49.7 IPS |
|
|
Text Classification (SP)
|
100% |
863
1.15 KIPS |
|
|
Text Classification (HP)
|
100% |
335
446.7 IPS |
|
|
Text Classification (Q)
|
97% |
473
633.1 IPS |
|
|
Machine Translation (SP)
|
100% |
1024
17.6 IPS |
|
|
Machine Translation (HP)
|
100% |
934
16.1 IPS |
|
|
Machine Translation (Q)
|
60% |
398
8.88 IPS |
