Micro-Star International Co., Ltd. Cyborg 15 AI A1VFK
Geekbench ML Score
9848
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | May 08 2024 03:55 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | Micro-Star International Co., Ltd. Cyborg 15 AI A1VFK |
| Motherboard | Micro-Star International Co., Ltd. MS-15K2 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 7 155H |
| Topology | 1 Processor, 16 Cores, 22 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 3.80 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| L1 Instruction Cache | 64.0 KB x 11 |
| L1 Data Cache | 48.0 KB x 11 |
| L2 Cache | 2.00 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% |
5080
950.6 IPS |
|
|
Image Classification (F16)
|
100% |
5100
954.3 IPS |
|
|
Image Classification (I8)
|
100% |
4463
835.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
7091
118.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
7030
117.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
6510
108.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
50492
61.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
51115
61.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
45732
55.4 IPS |
|
|
Object Detection (F32)
|
100% |
3943
294.4 IPS |
|
|
Object Detection (F16)
|
100% |
3632
271.2 IPS |
|
|
Object Detection (I8)
|
61% |
3440
256.8 IPS |
|
|
Face Detection (F32)
|
100% |
14879
176.9 IPS |
|
|
Face Detection (F16)
|
100% |
14689
174.7 IPS |
|
|
Face Detection (I8)
|
89% |
12424
147.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
21310
165.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
29236
226.7 IPS |
|
|
Depth Estimation (I8)
|
95% |
18520
143.6 IPS |
|
|
Style Transfer (F32)
|
100% |
110358
145.2 IPS |
|
|
Style Transfer (F16)
|
100% |
77410
101.8 IPS |
|
|
Style Transfer (I8)
|
98% |
71317
93.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
16616
593.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
16210
578.9 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
12562
448.6 IPS |
|
|
Text Classification (F32)
|
100% |
1727
2.48 KIPS |
|
|
Text Classification (F16)
|
100% |
1785
2.57 KIPS |
|
|
Text Classification (I8)
|
98% |
1043
1.50 KIPS |
|
|
Machine Translation (F32)
|
100% |
2927
53.9 IPS |
|
|
Machine Translation (F16)
|
100% |
2910
53.5 IPS |
|
|
Machine Translation (I8)
|
70% |
1640
30.2 IPS |
