motorola moto g power (2022)
Geekbench AI Score
125
Single Precision Score
122
Half Precision Score
89
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | January 01 2026 01:33 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM MT6765H |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | motorola moto g power (2022) |
| Model ID | motorola moto g power (2022) |
| Motherboard | tonga |
| 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 | 3.67 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
78
14.5 IPS |
|
|
Image Classification (HP)
|
100% |
81
15.1 IPS |
|
|
Image Classification (Q)
|
100% |
67
12.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
103
1.67 IPS |
|
|
Image Segmentation (HP)
|
100% |
103
1.67 IPS |
|
|
Image Segmentation (Q)
|
98% |
93
1.51 IPS |
|
|
Pose Estimation (SP)
|
100% |
431
0.50 IPS |
|
|
Pose Estimation (HP)
|
100% |
429
0.50 IPS |
|
|
Pose Estimation (Q)
|
96% |
411
0.48 IPS |
|
|
Object Detection (SP)
|
100% |
76
6.04 IPS |
|
|
Object Detection (HP)
|
100% |
76
6.03 IPS |
|
|
Object Detection (Q)
|
85% |
66
5.33 IPS |
|
|
Face Detection (SP)
|
100% |
224
2.66 IPS |
|
|
Face Detection (HP)
|
100% |
211
2.51 IPS |
|
|
Face Detection (Q)
|
97% |
174
2.08 IPS |
|
|
Depth Estimation (SP)
|
100% |
278
2.14 IPS |
|
|
Depth Estimation (HP)
|
99% |
261
2.01 IPS |
|
|
Depth Estimation (Q)
|
64% |
204
1.86 IPS |
|
|
Style Transfer (SP)
|
100% |
770
0.99 IPS |
|
|
Style Transfer (HP)
|
100% |
771
0.99 IPS |
|
|
Style Transfer (Q)
|
98% |
725
0.93 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
163
6.03 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
158
5.82 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
141
5.22 IPS |
|
|
Text Classification (SP)
|
35% |
7
66.8 IPS |
|
|
Text Classification (HP)
|
35% |
7
68.9 IPS |
|
|
Text Classification (Q)
|
32% |
5
60.2 IPS |
|
|
Machine Translation (SP)
|
100% |
68
1.17 IPS |
|
|
Machine Translation (HP)
|
100% |
59
1.02 IPS |
|
|
Machine Translation (Q)
|
41% |
11
0.73 IPS |
