Acer Aspire A514-52
Geekbench AI Score
1073
Single Precision Score
543
Half Precision Score
1422
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | kot-ubitsa |
| Upload Date | December 20 2024 08:30 PM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i5-10210U |
| System Information | |
|---|---|
| Operating System | Windows 10 Pro (64-bit) |
| Model | Acer Aspire A514-52 |
| Motherboard | CML Sneezy_WC |
| CPU Information | |
|---|---|
| Name | Intel Core i5-10210U |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 142 Stepping 12 |
| Base Frequency | 2.11 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
612
113.7 IPS |
|
|
Image Classification (HP)
|
100% |
185
34.4 IPS |
|
|
Image Classification (Q)
|
96% |
1112
207.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
342
5.55 IPS |
|
|
Image Segmentation (HP)
|
100% |
252
4.08 IPS |
|
|
Image Segmentation (Q)
|
97% |
643
10.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
1171
1.37 IPS |
|
|
Pose Estimation (HP)
|
100% |
1045
1.22 IPS |
|
|
Pose Estimation (Q)
|
86% |
2740
3.24 IPS |
|
|
Object Detection (SP)
|
100% |
941
74.7 IPS |
|
|
Object Detection (HP)
|
100% |
292
23.2 IPS |
|
|
Object Detection (Q)
|
58% |
999
109.2 IPS |
|
|
Face Detection (SP)
|
100% |
1509
17.9 IPS |
|
|
Face Detection (HP)
|
100% |
604
7.18 IPS |
|
|
Face Detection (Q)
|
96% |
2926
34.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
2016
15.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
841
6.48 IPS |
|
|
Depth Estimation (Q)
|
78% |
3284
26.2 IPS |
|
|
Style Transfer (SP)
|
100% |
4313
5.54 IPS |
|
|
Style Transfer (HP)
|
100% |
2790
3.59 IPS |
|
|
Style Transfer (Q)
|
87% |
5369
6.99 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
789
29.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
662
24.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1053
39.0 IPS |
|
|
Text Classification (SP)
|
100% |
940
1.25 KIPS |
|
|
Text Classification (HP)
|
100% |
448
597.3 IPS |
|
|
Text Classification (Q)
|
97% |
301
403.9 IPS |
|
|
Machine Translation (SP)
|
100% |
909
15.7 IPS |
|
|
Machine Translation (HP)
|
100% |
374
6.44 IPS |
|
|
Machine Translation (Q)
|
68% |
1061
20.5 IPS |
