motorola moto e13
Geekbench AI Score
53
Single Precision Score
74
Half Precision Score
72
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | September 24 2024 07:38 PM |
| Views | 38 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM Unisoc |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | motorola moto e13 |
| Model ID | motorola moto e13 |
| Motherboard | m170 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Unisoc |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 3 part 3338 revision 1 |
| Base Frequency | 1.61 GHz |
| Cluster 1 | 8 Cores @ 1.61 GHz |
| Memory Information | |
|---|---|
| Size | 1.78 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
33
6.20 IPS |
|
|
Image Classification (HP)
|
100% |
62
11.5 IPS |
|
|
Image Classification (Q)
|
99% |
61
11.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
48
0.78 IPS |
|
|
Image Segmentation (HP)
|
100% |
84
1.37 IPS |
|
|
Image Segmentation (Q)
|
98% |
83
1.35 IPS |
|
|
Pose Estimation (SP)
|
100% |
31
0.04 IPS |
|
|
Pose Estimation (HP)
|
100% |
37
0.04 IPS |
|
|
Pose Estimation (Q)
|
96% |
37
0.04 IPS |
|
|
Object Detection (SP)
|
100% |
28
2.21 IPS |
|
|
Object Detection (HP)
|
100% |
48
3.80 IPS |
|
|
Object Detection (Q)
|
83% |
47
3.83 IPS |
|
|
Face Detection (SP)
|
100% |
108
1.28 IPS |
|
|
Face Detection (HP)
|
100% |
163
1.94 IPS |
|
|
Face Detection (Q)
|
97% |
158
1.89 IPS |
|
|
Depth Estimation (SP)
|
100% |
59
0.46 IPS |
|
|
Depth Estimation (HP)
|
99% |
78
0.60 IPS |
|
|
Depth Estimation (Q)
|
62% |
63
0.60 IPS |
|
|
Style Transfer (SP)
|
100% |
117
0.15 IPS |
|
|
Style Transfer (HP)
|
100% |
161
0.21 IPS |
|
|
Style Transfer (Q)
|
98% |
160
0.21 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
31
1.13 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
47
1.74 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
47
1.73 IPS |
|
|
Text Classification (SP)
|
100% |
59
79.1 IPS |
|
|
Text Classification (HP)
|
100% |
59
79.1 IPS |
|
|
Text Classification (Q)
|
91% |
84
113.2 IPS |
|
|
Machine Translation (SP)
|
100% |
104
1.79 IPS |
|
|
Machine Translation (HP)
|
100% |
104
1.79 IPS |
|
|
Machine Translation (Q)
|
57% |
77
1.89 IPS |
