Micro-Star International Co., Ltd. Vector 16 HX AI A2XWIG
Geekbench AI Score
28409
Single Precision Score
48196
Half Precision Score
21961
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| Upload Date | July 14 2025 04:09 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5080 Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Micro-Star International Co., Ltd. Vector 16 HX AI A2XWIG |
| Motherboard | Micro-Star International Co., Ltd. MS-15M3 |
| 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% |
11351
2.11 KIPS |
|
|
Image Classification (HP)
|
100% |
17920
3.33 KIPS |
|
|
Image Classification (Q)
|
100% |
10218
1.90 KIPS |
|
|
Image Segmentation (SP)
|
100% |
21587
349.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
31702
513.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
19281
313.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
162687
189.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
442310
516.1 IPS |
|
|
Pose Estimation (Q)
|
96% |
145395
170.3 IPS |
|
|
Object Detection (SP)
|
100% |
14401
1.14 KIPS |
|
|
Object Detection (HP)
|
100% |
23856
1.89 KIPS |
|
|
Object Detection (Q)
|
86% |
11991
963.4 IPS |
|
|
Face Detection (SP)
|
100% |
41462
492.7 IPS |
|
|
Face Detection (HP)
|
100% |
58467
694.7 IPS |
|
|
Face Detection (Q)
|
97% |
35380
421.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
68770
529.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
121838
938.7 IPS |
|
|
Depth Estimation (Q)
|
78% |
52742
421.3 IPS |
|
|
Style Transfer (SP)
|
100% |
253420
325.8 IPS |
|
|
Style Transfer (HP)
|
100% |
856924
1.10 KIPS |
|
|
Style Transfer (Q)
|
98% |
221844
286.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
40045
1.48 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
69121
2.55 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
31856
1.18 KIPS |
|
|
Text Classification (SP)
|
100% |
3369
4.50 KIPS |
|
|
Text Classification (HP)
|
100% |
4301
5.74 KIPS |
|
|
Text Classification (Q)
|
97% |
2040
2.73 KIPS |
|
|
Machine Translation (SP)
|
100% |
6119
105.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6217
107.1 IPS |
|
|
Machine Translation (Q)
|
70% |
2825
53.0 IPS |
