Micro-Star International Co., Ltd. Prestige A16 AI+ A3HMG
Geekbench ML Score
6794
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | November 16 2024 03:18 PM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | Micro-Star International Co., Ltd. Prestige A16 AI+ A3HMG |
| Motherboard | Micro-Star International Co., Ltd. MS-159K |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen AI 9 365 w/ Radeon 880M |
| Topology | 1 Processor, 10 Cores, 20 Threads |
| Identifier | AuthenticAMD Family 26 Model 36 Stepping 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 6 Cores |
| L1 Instruction Cache | 32.0 KB x 10 |
| L1 Data Cache | 48.0 KB x 10 |
| L2 Cache | 1.00 MB x 10 |
| L3 Cache | 8.00 MB x 2 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | AMD Radeon(TM) 880M Graphics |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2718
508.7 IPS |
|
|
Image Classification (F16)
|
100% |
2769
518.1 IPS |
|
|
Image Classification (I8)
|
100% |
2208
413.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
3951
66.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
3927
65.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
3337
55.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
39134
47.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
40552
49.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
30901
37.4 IPS |
|
|
Object Detection (F32)
|
100% |
2025
151.2 IPS |
|
|
Object Detection (F16)
|
100% |
2200
164.2 IPS |
|
|
Object Detection (I8)
|
62% |
1974
147.4 IPS |
|
|
Face Detection (F32)
|
100% |
5988
71.2 IPS |
|
|
Face Detection (F16)
|
100% |
5931
70.5 IPS |
|
|
Face Detection (I8)
|
89% |
4608
54.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
17710
137.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
17373
134.7 IPS |
|
|
Depth Estimation (I8)
|
95% |
13487
104.6 IPS |
|
|
Style Transfer (F32)
|
100% |
69110
90.9 IPS |
|
|
Style Transfer (F16)
|
100% |
67870
89.3 IPS |
|
|
Style Transfer (I8)
|
98% |
48507
63.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
12731
454.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
10178
363.5 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
7886
281.6 IPS |
|
|
Text Classification (F32)
|
100% |
2205
3.17 KIPS |
|
|
Text Classification (F16)
|
100% |
2165
3.11 KIPS |
|
|
Text Classification (I8)
|
98% |
1596
2.29 KIPS |
|
|
Machine Translation (F32)
|
100% |
3446
63.4 IPS |
|
|
Machine Translation (F16)
|
100% |
3320
61.1 IPS |
|
|
Machine Translation (I8)
|
70% |
1802
33.2 IPS |
