Micro-Star International Co., Ltd. Cyborg 14 A13VF
Geekbench ML Score
1981
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 22 2024 06:15 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 | Intel(R) UHD Graphics |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1013
189.6 IPS |
|
|
Image Classification (F16)
|
100% |
981
183.5 IPS |
|
|
Image Classification (I8)
|
100% |
709
132.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
1309
21.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1356
22.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
1034
17.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
8889
10.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
8915
10.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
5016
6.07 IPS |
|
|
Object Detection (F32)
|
100% |
1034
77.2 IPS |
|
|
Object Detection (F16)
|
100% |
993
74.1 IPS |
|
|
Object Detection (I8)
|
54% |
792
59.1 IPS |
|
|
Face Detection (F32)
|
100% |
2092
24.9 IPS |
|
|
Face Detection (F16)
|
100% |
2044
24.3 IPS |
|
|
Face Detection (I8)
|
89% |
1423
16.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
4479
34.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
4525
35.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
3532
27.4 IPS |
|
|
Style Transfer (F32)
|
100% |
17912
23.6 IPS |
|
|
Style Transfer (F16)
|
100% |
17987
23.7 IPS |
|
|
Style Transfer (I8)
|
98% |
12487
16.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2746
98.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2748
98.1 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
1277
45.6 IPS |
|
|
Text Classification (F32)
|
100% |
887
1.28 KIPS |
|
|
Text Classification (F16)
|
100% |
838
1.20 KIPS |
|
|
Text Classification (I8)
|
98% |
459
659.5 IPS |
|
|
Machine Translation (F32)
|
100% |
846
15.6 IPS |
|
|
Machine Translation (F16)
|
100% |
874
16.1 IPS |
|
|
Machine Translation (I8)
|
70% |
459
8.45 IPS |
