motorola moto e22
Geekbench AI Score
226
Single Precision Score
232
Half Precision Score
241
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | benched |
| Upload Date | October 08 2024 07:34 PM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM MT6765H |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | motorola moto e22 |
| Model ID | motorola moto e22 |
| Motherboard | borag_retail |
| CPU Information | |
|---|---|
| Name | ARM MT6765H |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3331 revision 4 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.30 GHz |
| Memory Information | |
|---|---|
| Size | 3.72 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
101
18.8 IPS |
|
|
Image Classification (HP)
|
100% |
97
18.0 IPS |
|
|
Image Classification (Q)
|
100% |
126
23.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
137
2.22 IPS |
|
|
Image Segmentation (HP)
|
100% |
120
1.95 IPS |
|
|
Image Segmentation (Q)
|
98% |
210
3.41 IPS |
|
|
Pose Estimation (SP)
|
100% |
462
0.54 IPS |
|
|
Pose Estimation (HP)
|
100% |
470
0.55 IPS |
|
|
Pose Estimation (Q)
|
84% |
352
0.42 IPS |
|
|
Object Detection (SP)
|
100% |
82
6.53 IPS |
|
|
Object Detection (HP)
|
100% |
95
7.55 IPS |
|
|
Object Detection (Q)
|
83% |
135
10.9 IPS |
|
|
Face Detection (SP)
|
100% |
236
2.81 IPS |
|
|
Face Detection (HP)
|
100% |
345
4.10 IPS |
|
|
Face Detection (Q)
|
95% |
532
6.35 IPS |
|
|
Depth Estimation (SP)
|
100% |
447
3.44 IPS |
|
|
Depth Estimation (HP)
|
99% |
445
3.43 IPS |
|
|
Depth Estimation (Q)
|
64% |
448
4.10 IPS |
|
|
Style Transfer (SP)
|
89% |
1069
1.39 IPS |
|
|
Style Transfer (HP)
|
89% |
1110
1.44 IPS |
|
|
Style Transfer (Q)
|
98% |
1083
1.40 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
223
8.22 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
212
7.82 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
245
9.07 IPS |
|
|
Text Classification (SP)
|
100% |
139
185.9 IPS |
|
|
Text Classification (HP)
|
100% |
131
174.6 IPS |
|
|
Text Classification (Q)
|
88% |
125
168.3 IPS |
|
|
Machine Translation (SP)
|
100% |
190
3.28 IPS |
|
|
Machine Translation (HP)
|
100% |
185
3.19 IPS |
|
|
Machine Translation (Q)
|
50% |
69
2.46 IPS |
