Acer Aspire A315-34
Geekbench AI Score
168
Single Precision Score
92
Half Precision Score
298
Quantized Score
Geekbench AI 1.2.0 for Windows x86 (64-bit)
Result Information
| User | vladuna |
| Upload Date | February 21 2025 07:11 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Pentium Silver N5030 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Acer Aspire A315-34 |
| Motherboard | GLK Rose_GL |
| Power Plan | Acer |
| CPU Information | |
|---|---|
| Name | Intel Pentium Silver N5030 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 122 Stepping 8 |
| Base Frequency | 1.10 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 12.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
151
28.1 IPS |
|
|
Image Classification (HP)
|
100% |
40
7.35 IPS |
|
|
Image Classification (Q)
|
96% |
204
38.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
90
1.46 IPS |
|
|
Image Segmentation (HP)
|
100% |
64
1.04 IPS |
|
|
Image Segmentation (Q)
|
97% |
178
2.90 IPS |
|
|
Pose Estimation (SP)
|
100% |
202
0.24 IPS |
|
|
Pose Estimation (HP)
|
100% |
150
0.18 IPS |
|
|
Pose Estimation (Q)
|
86% |
470
0.56 IPS |
|
|
Object Detection (SP)
|
100% |
96
7.60 IPS |
|
|
Object Detection (HP)
|
100% |
47
3.75 IPS |
|
|
Object Detection (Q)
|
58% |
160
17.5 IPS |
|
|
Face Detection (SP)
|
100% |
285
3.39 IPS |
|
|
Face Detection (HP)
|
100% |
122
1.45 IPS |
|
|
Face Detection (Q)
|
96% |
454
5.41 IPS |
|
|
Depth Estimation (SP)
|
100% |
257
1.98 IPS |
|
|
Depth Estimation (HP)
|
99% |
135
1.04 IPS |
|
|
Depth Estimation (Q)
|
78% |
480
3.82 IPS |
|
|
Style Transfer (SP)
|
100% |
523
0.67 IPS |
|
|
Style Transfer (HP)
|
100% |
423
0.54 IPS |
|
|
Style Transfer (Q)
|
87% |
922
1.20 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
111
4.11 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
84
3.11 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
221
8.20 IPS |
|
|
Text Classification (SP)
|
100% |
95
126.2 IPS |
|
|
Text Classification (HP)
|
100% |
62
82.3 IPS |
|
|
Text Classification (Q)
|
97% |
203
271.7 IPS |
|
|
Machine Translation (SP)
|
100% |
174
3.00 IPS |
|
|
Machine Translation (HP)
|
100% |
73
1.25 IPS |
|
|
Machine Translation (Q)
|
68% |
232
4.47 IPS |
