Micro-Star International Co., Ltd. Thin GF63 12VE
Geekbench ML Score
1360
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | April 26 2024 04:55 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | Micro-Star International Co., Ltd. Thin GF63 12VE |
| Motherboard | Micro-Star International Co., Ltd. MS-16R8 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i5-12450H |
| Topology | 1 Processor, 8 Cores, 12 Threads |
| Identifier | GenuineIntel Family 6 Model 154 Stepping 3 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 32.0 KB x 6 |
| L1 Data Cache | 48.0 KB x 6 |
| L2 Cache | 1.25 MB x 1 |
| L3 Cache | 12.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) UHD Graphics |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
675
126.3 IPS |
|
|
Image Classification (F16)
|
100% |
669
125.2 IPS |
|
|
Image Classification (I8)
|
100% |
538
100.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
980
16.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
959
16.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
701
11.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
5308
6.43 IPS |
|
|
Pose Estimation (F16)
|
100% |
5394
6.53 IPS |
|
|
Pose Estimation (I8)
|
100% |
3405
4.12 IPS |
|
|
Object Detection (F32)
|
100% |
672
50.2 IPS |
|
|
Object Detection (F16)
|
100% |
751
56.1 IPS |
|
|
Object Detection (I8)
|
54% |
604
45.1 IPS |
|
|
Face Detection (F32)
|
100% |
1439
17.1 IPS |
|
|
Face Detection (F16)
|
100% |
1445
17.2 IPS |
|
|
Face Detection (I8)
|
89% |
986
11.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
3091
24.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
3099
24.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
2279
17.7 IPS |
|
|
Style Transfer (F32)
|
100% |
11333
14.9 IPS |
|
|
Style Transfer (F16)
|
100% |
11317
14.9 IPS |
|
|
Style Transfer (I8)
|
98% |
8212
10.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1794
64.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1849
66.0 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
909
32.5 IPS |
|
|
Text Classification (F32)
|
100% |
647
929.4 IPS |
|
|
Text Classification (F16)
|
100% |
589
846.9 IPS |
|
|
Text Classification (I8)
|
98% |
304
437.5 IPS |
|
|
Machine Translation (F32)
|
100% |
571
10.5 IPS |
|
|
Machine Translation (F16)
|
100% |
615
11.3 IPS |
|
|
Machine Translation (I8)
|
70% |
371
6.82 IPS |
