Micro-Star International Co., Ltd. GF63 Thin 10UC
Geekbench ML Score
5601
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 16 2024 08:33 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 | DirectML |
| Device | NVIDIA GeForce RTX 3050 Laptop GPU |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
3041
569.0 IPS |
|
|
Image Classification (F16)
|
100% |
3071
574.6 IPS |
|
|
Image Classification (I8)
|
100% |
2388
446.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
3070
51.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
2966
49.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
2855
47.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
24855
30.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
33667
40.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
24152
29.2 IPS |
|
|
Object Detection (F32)
|
100% |
2061
153.9 IPS |
|
|
Object Detection (F16)
|
100% |
2560
191.1 IPS |
|
|
Object Detection (I8)
|
61% |
2232
166.7 IPS |
|
|
Face Detection (F32)
|
100% |
7194
85.5 IPS |
|
|
Face Detection (F16)
|
100% |
7233
86.0 IPS |
|
|
Face Detection (I8)
|
89% |
5800
69.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
15324
118.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
14790
114.7 IPS |
|
|
Depth Estimation (I8)
|
95% |
12656
98.1 IPS |
|
|
Style Transfer (F32)
|
100% |
52674
69.3 IPS |
|
|
Style Transfer (F16)
|
100% |
54088
71.1 IPS |
|
|
Style Transfer (I8)
|
98% |
49016
64.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
10119
361.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
8702
310.8 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
5574
199.1 IPS |
|
|
Text Classification (F32)
|
100% |
1014
1.46 KIPS |
|
|
Text Classification (F16)
|
100% |
1442
2.07 KIPS |
|
|
Text Classification (I8)
|
98% |
853
1.23 KIPS |
|
|
Machine Translation (F32)
|
100% |
1676
30.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1686
31.0 IPS |
|
|
Machine Translation (I8)
|
70% |
977
18.0 IPS |
