Micro-Star International Co., Ltd. Vector 16 HX AI A2XWIG
Geekbench ML Score
5919
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 02:33 PM |
| Views | 2 |
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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
3056
571.8 IPS |
|
|
Image Classification (F16)
|
100% |
3004
562.2 IPS |
|
|
Image Classification (I8)
|
99% |
5044
943.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
2368
39.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
2346
39.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
3842
64.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
15590
18.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
15396
18.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
49240
59.6 IPS |
|
|
Object Detection (F32)
|
100% |
2875
214.6 IPS |
|
|
Object Detection (F16)
|
100% |
2917
217.8 IPS |
|
|
Object Detection (I8)
|
62% |
2726
203.5 IPS |
|
|
Face Detection (F32)
|
100% |
5046
60.0 IPS |
|
|
Face Detection (F16)
|
100% |
4983
59.3 IPS |
|
|
Face Detection (I8)
|
89% |
5553
66.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
12778
99.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
12927
100.2 IPS |
|
|
Depth Estimation (I8)
|
96% |
21616
167.6 IPS |
|
|
Style Transfer (F32)
|
100% |
32868
43.2 IPS |
|
|
Style Transfer (F16)
|
100% |
33039
43.5 IPS |
|
|
Style Transfer (I8)
|
98% |
24159
31.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5837
208.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
6038
215.6 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
7528
268.8 IPS |
|
|
Text Classification (F32)
|
100% |
1827
2.63 KIPS |
|
|
Text Classification (F16)
|
100% |
1835
2.64 KIPS |
|
|
Text Classification (I8)
|
98% |
1385
1.99 KIPS |
|
|
Machine Translation (F32)
|
100% |
2837
52.2 IPS |
|
|
Machine Translation (F16)
|
100% |
2846
52.4 IPS |
|
|
Machine Translation (I8)
|
67% |
4250
78.2 IPS |
