motorola moto e32(s)
Geekbench AI Score
41
Single Precision Score
41
Half Precision Score
67
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | benched |
| Upload Date | October 08 2024 08:20 PM |
| Views | 13 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM MT6765H |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | motorola moto e32(s) |
| Model ID | motorola moto e32(s) |
| Motherboard | p410ae |
| 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 | 3.68 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
23
4.36 IPS |
|
|
Image Classification (HP)
|
100% |
24
4.40 IPS |
|
|
Image Classification (Q)
|
99% |
42
7.87 IPS |
|
|
Image Segmentation (SP)
|
100% |
32
0.52 IPS |
|
|
Image Segmentation (HP)
|
100% |
32
0.52 IPS |
|
|
Image Segmentation (Q)
|
98% |
50
0.81 IPS |
|
|
Pose Estimation (SP)
|
100% |
46
0.05 IPS |
|
|
Pose Estimation (HP)
|
100% |
46
0.05 IPS |
|
|
Pose Estimation (Q)
|
98% |
88
0.10 IPS |
|
|
Object Detection (SP)
|
100% |
25
1.98 IPS |
|
|
Object Detection (HP)
|
100% |
26
2.03 IPS |
|
|
Object Detection (Q)
|
87% |
44
3.56 IPS |
|
|
Face Detection (SP)
|
100% |
58
0.68 IPS |
|
|
Face Detection (HP)
|
100% |
58
0.68 IPS |
|
|
Face Detection (Q)
|
97% |
109
1.30 IPS |
|
|
Depth Estimation (SP)
|
100% |
56
0.43 IPS |
|
|
Depth Estimation (HP)
|
99% |
56
0.43 IPS |
|
|
Depth Estimation (Q)
|
64% |
86
0.78 IPS |
|
|
Style Transfer (SP)
|
100% |
95
0.12 IPS |
|
|
Style Transfer (HP)
|
100% |
96
0.12 IPS |
|
|
Style Transfer (Q)
|
98% |
197
0.25 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
29
1.07 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
29
1.07 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
54
2.01 IPS |
|
|
Text Classification (SP)
|
100% |
33
44.7 IPS |
|
|
Text Classification (HP)
|
100% |
34
44.8 IPS |
|
|
Text Classification (Q)
|
91% |
50
67.4 IPS |
|
|
Machine Translation (SP)
|
100% |
59
1.02 IPS |
|
|
Machine Translation (HP)
|
100% |
59
1.02 IPS |
|
|
Machine Translation (Q)
|
57% |
47
1.15 IPS |
