Micro-Star International Co., Ltd. Vector 16 HX AI A2XWIG
Geekbench AI Score
28114
Single Precision Score
47836
Half Precision Score
21742
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | hitch22 |
| Upload Date | July 18 2025 11:20 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5080 Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. Vector 16 HX AI A2XWIG |
| Motherboard | Micro-Star International Co., Ltd. MS-15M3 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 9 275HX |
| Topology | 1 Processor, 24 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 2.70 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
11178
2.08 KIPS |
|
|
Image Classification (HP)
|
100% |
17674
3.29 KIPS |
|
|
Image Classification (Q)
|
100% |
10121
1.88 KIPS |
|
|
Image Segmentation (SP)
|
100% |
20988
340.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
31293
507.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
19195
312.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
160902
187.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
441185
514.8 IPS |
|
|
Pose Estimation (Q)
|
96% |
144121
168.8 IPS |
|
|
Object Detection (SP)
|
100% |
14131
1.12 KIPS |
|
|
Object Detection (HP)
|
100% |
23616
1.87 KIPS |
|
|
Object Detection (Q)
|
86% |
11778
946.3 IPS |
|
|
Face Detection (SP)
|
100% |
41376
491.6 IPS |
|
|
Face Detection (HP)
|
100% |
58683
697.3 IPS |
|
|
Face Detection (Q)
|
97% |
35127
418.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
68425
527.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
122359
942.7 IPS |
|
|
Depth Estimation (Q)
|
78% |
52679
420.8 IPS |
|
|
Style Transfer (SP)
|
100% |
257332
330.8 IPS |
|
|
Style Transfer (HP)
|
100% |
848651
1.09 KIPS |
|
|
Style Transfer (Q)
|
98% |
219781
283.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
39744
1.47 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
68112
2.52 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
31642
1.17 KIPS |
|
|
Text Classification (SP)
|
100% |
3291
4.39 KIPS |
|
|
Text Classification (HP)
|
100% |
4246
5.67 KIPS |
|
|
Text Classification (Q)
|
97% |
2014
2.70 KIPS |
|
|
Machine Translation (SP)
|
100% |
6070
104.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6179
106.4 IPS |
|
|
Machine Translation (Q)
|
70% |
2763
51.8 IPS |
