Acer Swift SF114-32
Geekbench AI Score
215
Single Precision Score
118
Half Precision Score
385
Quantized Score
Geekbench AI 1.3.0 for Windows x86 (64-bit)
Result Information
| User | Nickayz |
| Upload Date | March 21 2025 02:07 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Pentium Silver N5000 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Acer Swift SF114-32 |
| Motherboard | GLK Sapporo_GL |
| Power Plan | Ausbalanciert |
| CPU Information | |
|---|---|
| Name | Intel Pentium Silver N5000 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 122 Stepping 1 |
| Base Frequency | 1.10 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 4.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
161
30.0 IPS |
|
|
Image Classification (HP)
|
100% |
50
9.28 IPS |
|
|
Image Classification (Q)
|
96% |
262
48.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
107
1.73 IPS |
|
|
Image Segmentation (HP)
|
100% |
71
1.14 IPS |
|
|
Image Segmentation (Q)
|
97% |
227
3.69 IPS |
|
|
Pose Estimation (SP)
|
100% |
229
0.27 IPS |
|
|
Pose Estimation (HP)
|
100% |
172
0.20 IPS |
|
|
Pose Estimation (Q)
|
86% |
543
0.64 IPS |
|
|
Object Detection (SP)
|
100% |
135
10.7 IPS |
|
|
Object Detection (HP)
|
100% |
62
4.94 IPS |
|
|
Object Detection (Q)
|
58% |
213
23.2 IPS |
|
|
Face Detection (SP)
|
100% |
366
4.35 IPS |
|
|
Face Detection (HP)
|
100% |
152
1.81 IPS |
|
|
Face Detection (Q)
|
96% |
558
6.65 IPS |
|
|
Depth Estimation (SP)
|
100% |
343
2.64 IPS |
|
|
Depth Estimation (HP)
|
99% |
175
1.35 IPS |
|
|
Depth Estimation (Q)
|
78% |
606
4.82 IPS |
|
|
Style Transfer (SP)
|
100% |
626
0.80 IPS |
|
|
Style Transfer (HP)
|
100% |
526
0.68 IPS |
|
|
Style Transfer (Q)
|
87% |
1053
1.37 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
147
5.43 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
114
4.21 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
300
11.1 IPS |
|
|
Text Classification (SP)
|
100% |
148
196.9 IPS |
|
|
Text Classification (HP)
|
100% |
96
127.5 IPS |
|
|
Text Classification (Q)
|
97% |
292
391.6 IPS |
|
|
Machine Translation (SP)
|
100% |
241
4.14 IPS |
|
|
Machine Translation (HP)
|
100% |
96
1.65 IPS |
|
|
Machine Translation (Q)
|
68% |
342
6.60 IPS |
