Micro-Star International Co., Ltd. Thin A15 B7VF
Geekbench ML Score
9917
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 19 2024 10:36 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | Micro-Star International Co., Ltd. Thin A15 B7VF |
| Motherboard | Micro-Star International Co., Ltd. MS-16RK |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 7 7735HS |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 68 Stepping 1 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 8 |
| L1 Data Cache | 32.0 KB x 8 |
| L2 Cache | 512 KB x 8 |
| L3 Cache | 16.0 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% |
5193
971.7 IPS |
|
|
Image Classification (F16)
|
100% |
5105
955.3 IPS |
|
|
Image Classification (I8)
|
100% |
4694
878.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
6943
116.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
7220
120.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
6386
106.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
50959
61.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
51236
62.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
49407
59.8 IPS |
|
|
Object Detection (F32)
|
100% |
3613
269.7 IPS |
|
|
Object Detection (F16)
|
100% |
3295
246.0 IPS |
|
|
Object Detection (I8)
|
61% |
3485
260.2 IPS |
|
|
Face Detection (F32)
|
100% |
15042
178.9 IPS |
|
|
Face Detection (F16)
|
100% |
14737
175.2 IPS |
|
|
Face Detection (I8)
|
89% |
12438
147.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
21709
168.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
29605
229.6 IPS |
|
|
Depth Estimation (I8)
|
94% |
21051
163.3 IPS |
|
|
Style Transfer (F32)
|
100% |
108457
142.7 IPS |
|
|
Style Transfer (F16)
|
100% |
78133
102.8 IPS |
|
|
Style Transfer (I8)
|
98% |
81461
107.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
17914
639.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
15796
564.1 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
12067
430.9 IPS |
|
|
Text Classification (F32)
|
100% |
1690
2.43 KIPS |
|
|
Text Classification (F16)
|
100% |
1704
2.45 KIPS |
|
|
Text Classification (I8)
|
98% |
1110
1.60 KIPS |
|
|
Machine Translation (F32)
|
100% |
2815
51.8 IPS |
|
|
Machine Translation (F16)
|
100% |
2845
52.4 IPS |
|
|
Machine Translation (I8)
|
70% |
1623
29.9 IPS |
