motorola moto g power (2022)
Geekbench AI Score
44
Single Precision Score
44
Half Precision Score
69
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | January 01 2026 09:36 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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% |
25
4.67 IPS |
|
|
Image Classification (HP)
|
100% |
25
4.70 IPS |
|
|
Image Classification (Q)
|
99% |
44
8.19 IPS |
|
|
Image Segmentation (SP)
|
100% |
34
0.55 IPS |
|
|
Image Segmentation (HP)
|
100% |
34
0.55 IPS |
|
|
Image Segmentation (Q)
|
98% |
50
0.82 IPS |
|
|
Pose Estimation (SP)
|
100% |
50
0.06 IPS |
|
|
Pose Estimation (HP)
|
100% |
50
0.06 IPS |
|
|
Pose Estimation (Q)
|
98% |
90
0.10 IPS |
|
|
Object Detection (SP)
|
100% |
26
2.07 IPS |
|
|
Object Detection (HP)
|
100% |
26
2.07 IPS |
|
|
Object Detection (Q)
|
87% |
46
3.69 IPS |
|
|
Face Detection (SP)
|
100% |
61
0.73 IPS |
|
|
Face Detection (HP)
|
100% |
62
0.73 IPS |
|
|
Face Detection (Q)
|
97% |
111
1.33 IPS |
|
|
Depth Estimation (SP)
|
100% |
59
0.45 IPS |
|
|
Depth Estimation (HP)
|
99% |
59
0.45 IPS |
|
|
Depth Estimation (Q)
|
64% |
89
0.81 IPS |
|
|
Style Transfer (SP)
|
100% |
106
0.14 IPS |
|
|
Style Transfer (HP)
|
100% |
106
0.14 IPS |
|
|
Style Transfer (Q)
|
98% |
204
0.26 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
31
1.15 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
31
1.15 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
55
2.04 IPS |
|
|
Text Classification (SP)
|
100% |
36
47.6 IPS |
|
|
Text Classification (HP)
|
100% |
36
47.6 IPS |
|
|
Text Classification (Q)
|
91% |
51
69.2 IPS |
|
|
Machine Translation (SP)
|
100% |
64
1.10 IPS |
|
|
Machine Translation (HP)
|
100% |
63
1.09 IPS |
|
|
Machine Translation (Q)
|
57% |
50
1.23 IPS |
