Micro-Star International Co., Ltd. GF63 Thin 10UC
Geekbench ML Score
1300
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 16 2024 08:36 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | Micro-Star International Co., Ltd. GF63 Thin 10UC |
| Motherboard | Micro-Star International Co., Ltd. MS-16R5 |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Core i5-10500H |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | GenuineIntel Family 6 Model 165 Stepping 2 |
| Base Frequency | 2.50 GHz |
| Cluster 1 | 6 Cores |
| L1 Instruction Cache | 32.0 KB x 6 |
| L1 Data Cache | 32.0 KB x 6 |
| L2 Cache | 256 KB x 6 |
| L3 Cache | 12.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
774
144.8 IPS |
|
|
Image Classification (F16)
|
100% |
817
152.9 IPS |
|
|
Image Classification (I8)
|
97% |
1411
264.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
529
8.83 IPS |
|
|
Image Segmentation (F16)
|
100% |
519
8.66 IPS |
|
|
Image Segmentation (I8)
|
97% |
1012
16.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
2193
2.66 IPS |
|
|
Pose Estimation (F16)
|
100% |
2066
2.50 IPS |
|
|
Pose Estimation (I8)
|
100% |
4846
5.87 IPS |
|
|
Object Detection (F32)
|
100% |
702
52.4 IPS |
|
|
Object Detection (F16)
|
100% |
665
49.6 IPS |
|
|
Object Detection (I8)
|
60% |
761
56.8 IPS |
|
|
Face Detection (F32)
|
100% |
920
10.9 IPS |
|
|
Face Detection (F16)
|
100% |
864
10.3 IPS |
|
|
Face Detection (I8)
|
87% |
1679
20.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
2297
17.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
2263
17.6 IPS |
|
|
Depth Estimation (I8)
|
74% |
4749
36.8 IPS |
|
|
Style Transfer (F32)
|
100% |
5051
6.64 IPS |
|
|
Style Transfer (F16)
|
100% |
4688
6.17 IPS |
|
|
Style Transfer (I8)
|
85% |
5611
7.38 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1170
41.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1131
40.4 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
1572
56.1 IPS |
|
|
Text Classification (F32)
|
100% |
800
1.15 KIPS |
|
|
Text Classification (F16)
|
100% |
911
1.31 KIPS |
|
|
Text Classification (I8)
|
94% |
293
420.9 IPS |
|
|
Machine Translation (F32)
|
100% |
810
14.9 IPS |
|
|
Machine Translation (F16)
|
100% |
814
15.0 IPS |
|
|
Machine Translation (I8)
|
67% |
1065
19.6 IPS |
