Micro-Star International Co., Ltd. Thin GF63 12VE
Geekbench ML Score
8673
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | April 26 2024 04:44 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 | NVIDIA GeForce RTX 4050 Laptop GPU |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
3355
627.7 IPS |
|
|
Image Classification (F16)
|
100% |
4318
807.9 IPS |
|
|
Image Classification (I8)
|
100% |
3707
693.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
6313
105.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
6399
106.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
5411
90.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
43281
52.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
44244
53.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
48593
58.8 IPS |
|
|
Object Detection (F32)
|
100% |
3013
224.9 IPS |
|
|
Object Detection (F16)
|
100% |
3252
242.8 IPS |
|
|
Object Detection (I8)
|
61% |
3266
243.8 IPS |
|
|
Face Detection (F32)
|
100% |
10453
124.3 IPS |
|
|
Face Detection (F16)
|
100% |
10306
122.5 IPS |
|
|
Face Detection (I8)
|
89% |
10249
121.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
21375
165.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
24622
190.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
21005
162.9 IPS |
|
|
Style Transfer (F32)
|
100% |
73617
96.8 IPS |
|
|
Style Transfer (F16)
|
100% |
71680
94.3 IPS |
|
|
Style Transfer (I8)
|
98% |
69018
90.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
15788
563.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
15735
562.0 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
11091
396.1 IPS |
|
|
Text Classification (F32)
|
100% |
1846
2.65 KIPS |
|
|
Text Classification (F16)
|
100% |
1895
2.72 KIPS |
|
|
Text Classification (I8)
|
98% |
1089
1.57 KIPS |
|
|
Machine Translation (F32)
|
100% |
2554
47.0 IPS |
|
|
Machine Translation (F16)
|
100% |
2420
44.5 IPS |
|
|
Machine Translation (I8)
|
70% |
1388
25.5 IPS |
