Micro-Star International Co., Ltd. Vector 16 HX AI A2XWIG
Geekbench AI Score
28243
Single Precision Score
47878
Half Precision Score
21690
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | hitch22 |
| Upload Date | July 18 2025 11:01 AM |
| Views | 5 |
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% |
11234
2.09 KIPS |
|
|
Image Classification (HP)
|
100% |
18076
3.36 KIPS |
|
|
Image Classification (Q)
|
100% |
10068
1.87 KIPS |
|
|
Image Segmentation (SP)
|
100% |
21497
348.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
31793
515.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
19240
312.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
161488
188.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
436823
509.7 IPS |
|
|
Pose Estimation (Q)
|
96% |
143437
168.0 IPS |
|
|
Object Detection (SP)
|
100% |
14295
1.13 KIPS |
|
|
Object Detection (HP)
|
100% |
23620
1.87 KIPS |
|
|
Object Detection (Q)
|
86% |
11993
963.6 IPS |
|
|
Face Detection (SP)
|
100% |
41093
488.3 IPS |
|
|
Face Detection (HP)
|
100% |
58363
693.5 IPS |
|
|
Face Detection (Q)
|
97% |
35233
420.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
68983
531.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
121867
938.9 IPS |
|
|
Depth Estimation (Q)
|
78% |
51970
415.2 IPS |
|
|
Style Transfer (SP)
|
100% |
254983
327.8 IPS |
|
|
Style Transfer (HP)
|
100% |
841254
1.08 KIPS |
|
|
Style Transfer (Q)
|
98% |
212417
273.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
39725
1.47 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
68954
2.55 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
31635
1.17 KIPS |
|
|
Text Classification (SP)
|
100% |
3323
4.44 KIPS |
|
|
Text Classification (HP)
|
100% |
4214
5.62 KIPS |
|
|
Text Classification (Q)
|
97% |
2010
2.69 KIPS |
|
|
Machine Translation (SP)
|
100% |
6071
104.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6140
105.8 IPS |
|
|
Machine Translation (Q)
|
70% |
2797
52.5 IPS |
