Micro-Star International Co., Ltd. Vector 16 HX AI A2XWIG
Geekbench ML Score
21923
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 02:38 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (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 |
| L1 Instruction Cache | 64.0 KB x 12 |
| L1 Data Cache | 48.0 KB x 12 |
| L2 Cache | 3.00 MB x 3 |
| L3 Cache | 36.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5080 Laptop GPU |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
10012
1.87 KIPS |
|
|
Image Classification (F16)
|
100% |
10203
1.91 KIPS |
|
|
Image Classification (I8)
|
100% |
8928
1.67 KIPS |
|
|
Image Segmentation (F32)
|
100% |
15727
262.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
16109
269.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
14275
238.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
156430
189.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
156747
189.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
129250
156.5 IPS |
|
|
Object Detection (F32)
|
100% |
7630
569.7 IPS |
|
|
Object Detection (F16)
|
100% |
7630
569.6 IPS |
|
|
Object Detection (I8)
|
50% |
7070
527.8 IPS |
|
|
Face Detection (F32)
|
100% |
32455
385.9 IPS |
|
|
Face Detection (F16)
|
100% |
33699
400.7 IPS |
|
|
Face Detection (I8)
|
89% |
28796
342.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
64493
500.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
68203
528.9 IPS |
|
|
Depth Estimation (I8)
|
94% |
55192
428.0 IPS |
|
|
Style Transfer (F32)
|
100% |
247625
325.7 IPS |
|
|
Style Transfer (F16)
|
100% |
251057
330.2 IPS |
|
|
Style Transfer (I8)
|
98% |
218236
287.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
35108
1.25 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
37537
1.34 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
30754
1.10 KIPS |
|
|
Text Classification (F32)
|
100% |
2987
4.29 KIPS |
|
|
Text Classification (F16)
|
100% |
2948
4.24 KIPS |
|
|
Text Classification (I8)
|
98% |
1814
2.61 KIPS |
|
|
Machine Translation (F32)
|
100% |
4549
83.7 IPS |
|
|
Machine Translation (F16)
|
100% |
4621
85.0 IPS |
|
|
Machine Translation (I8)
|
70% |
2779
51.1 IPS |
