Micro-Star International Co., Ltd. Cyborg 14 A13VF
Geekbench ML Score
10330
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 22 2024 06:07 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% |
4971
930.3 IPS |
|
|
Image Classification (F16)
|
100% |
5190
971.2 IPS |
|
|
Image Classification (I8)
|
100% |
4357
815.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
8702
145.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
7184
120.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
6310
105.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
51279
62.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
60149
72.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
45894
55.6 IPS |
|
|
Object Detection (F32)
|
100% |
4290
320.3 IPS |
|
|
Object Detection (F16)
|
100% |
4435
331.1 IPS |
|
|
Object Detection (I8)
|
61% |
4236
316.2 IPS |
|
|
Face Detection (F32)
|
100% |
14477
172.1 IPS |
|
|
Face Detection (F16)
|
100% |
14810
176.1 IPS |
|
|
Face Detection (I8)
|
89% |
13093
155.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
30326
235.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
29867
231.6 IPS |
|
|
Depth Estimation (I8)
|
94% |
26178
203.0 IPS |
|
|
Style Transfer (F32)
|
100% |
111637
146.8 IPS |
|
|
Style Transfer (F16)
|
100% |
79188
104.2 IPS |
|
|
Style Transfer (I8)
|
98% |
71974
94.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
16122
575.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
16012
571.8 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
11857
423.4 IPS |
|
|
Text Classification (F32)
|
100% |
1761
2.53 KIPS |
|
|
Text Classification (F16)
|
100% |
1804
2.59 KIPS |
|
|
Text Classification (I8)
|
98% |
979
1.41 KIPS |
|
|
Machine Translation (F32)
|
100% |
2851
52.5 IPS |
|
|
Machine Translation (F16)
|
100% |
2835
52.2 IPS |
|
|
Machine Translation (I8)
|
70% |
1608
29.6 IPS |
