Micro-Star International Co., Ltd. Cyborg 14 A13VF
Geekbench ML Score
10192
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 22 2024 06:10 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Micro-Star International Co., Ltd. Cyborg 14 A13VF |
| Motherboard | Micro-Star International Co., Ltd. MS-14P1 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-13620H |
| Topology | 1 Processor, 10 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 186 Stepping 2 |
| Base Frequency | 2.40 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 32.0 KB x 8 |
| L1 Data Cache | 48.0 KB x 8 |
| L2 Cache | 1.25 MB x 2 |
| L3 Cache | 24.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4060 Laptop GPU |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
4641
868.4 IPS |
|
|
Image Classification (F16)
|
100% |
4820
901.9 IPS |
|
|
Image Classification (I8)
|
100% |
4337
811.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
8653
144.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
7037
117.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
6352
106.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
48917
59.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
56041
67.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
54586
66.1 IPS |
|
|
Object Detection (F32)
|
100% |
4445
331.8 IPS |
|
|
Object Detection (F16)
|
100% |
3798
283.5 IPS |
|
|
Object Detection (I8)
|
61% |
3916
292.3 IPS |
|
|
Face Detection (F32)
|
100% |
14381
171.0 IPS |
|
|
Face Detection (F16)
|
100% |
13516
160.7 IPS |
|
|
Face Detection (I8)
|
89% |
12070
143.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
30348
235.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
30225
234.4 IPS |
|
|
Depth Estimation (I8)
|
94% |
25848
200.5 IPS |
|
|
Style Transfer (F32)
|
100% |
112809
148.4 IPS |
|
|
Style Transfer (F16)
|
100% |
79069
104.0 IPS |
|
|
Style Transfer (I8)
|
98% |
69846
91.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
17101
610.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
16124
575.8 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
11966
427.4 IPS |
|
|
Text Classification (F32)
|
100% |
1772
2.55 KIPS |
|
|
Text Classification (F16)
|
100% |
1790
2.57 KIPS |
|
|
Text Classification (I8)
|
98% |
1050
1.51 KIPS |
|
|
Machine Translation (F32)
|
100% |
2788
51.3 IPS |
|
|
Machine Translation (F16)
|
100% |
2830
52.1 IPS |
|
|
Machine Translation (I8)
|
70% |
1590
29.3 IPS |
