Micro-Star International Co., Ltd. Vector 17 HX AI A2XWIG
Geekbench AI Score
27348
Single Precision Score
47584
Half Precision Score
21304
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| User | teknoseyir |
| Upload Date | July 10 2025 02:11 PM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5080 Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | Micro-Star International Co., Ltd. Vector 17 HX AI A2XWIG |
| Motherboard | Micro-Star International Co., Ltd. MS-17S3 |
| Power Plan | Dengeli |
| 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 | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
11162
2.08 KIPS |
|
|
Image Classification (HP)
|
100% |
18001
3.35 KIPS |
|
|
Image Classification (Q)
|
100% |
9972
1.85 KIPS |
|
|
Image Segmentation (SP)
|
100% |
21294
345.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
31680
513.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
19033
309.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
148152
172.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
419943
490.0 IPS |
|
|
Pose Estimation (Q)
|
96% |
134855
158.0 IPS |
|
|
Object Detection (SP)
|
100% |
14244
1.13 KIPS |
|
|
Object Detection (HP)
|
100% |
23947
1.90 KIPS |
|
|
Object Detection (Q)
|
86% |
11786
946.9 IPS |
|
|
Face Detection (SP)
|
100% |
41306
490.8 IPS |
|
|
Face Detection (HP)
|
100% |
59573
707.9 IPS |
|
|
Face Detection (Q)
|
97% |
35169
419.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
65094
501.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
120689
929.8 IPS |
|
|
Depth Estimation (Q)
|
78% |
51517
411.5 IPS |
|
|
Style Transfer (SP)
|
100% |
236327
303.8 IPS |
|
|
Style Transfer (HP)
|
100% |
815955
1.05 KIPS |
|
|
Style Transfer (Q)
|
98% |
206694
266.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
37707
1.39 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
67996
2.51 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
30697
1.14 KIPS |
|
|
Text Classification (SP)
|
100% |
3259
4.35 KIPS |
|
|
Text Classification (HP)
|
100% |
4223
5.64 KIPS |
|
|
Text Classification (Q)
|
97% |
2001
2.68 KIPS |
|
|
Machine Translation (SP)
|
100% |
5976
102.9 IPS |
|
|
Machine Translation (HP)
|
100% |
6161
106.1 IPS |
|
|
Machine Translation (Q)
|
70% |
2776
52.1 IPS |
