motorola motorola edge plus 2023
Geekbench AI Score
1567
Single Precision Score
2579
Half Precision Score
2166
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | Michaelandroid |
| Upload Date | August 28 2025 03:12 AM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | motorola motorola edge plus 2023 |
| Model ID | motorola motorola edge plus 2023 |
| Motherboard | rtwo |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.19 GHz |
| Memory Information | |
|---|---|
| Size | 7.13 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
960
178.5 IPS |
|
|
Image Classification (HP)
|
100% |
1761
327.4 IPS |
|
|
Image Classification (Q)
|
99% |
1659
309.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
2234
36.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
4037
65.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
3823
62.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
7912
9.23 IPS |
|
|
Pose Estimation (HP)
|
99% |
14130
16.5 IPS |
|
|
Pose Estimation (Q)
|
97% |
13636
16.0 IPS |
|
|
Object Detection (SP)
|
100% |
743
58.9 IPS |
|
|
Object Detection (HP)
|
99% |
1385
109.9 IPS |
|
|
Object Detection (Q)
|
82% |
1312
106.3 IPS |
|
|
Face Detection (SP)
|
100% |
2781
33.0 IPS |
|
|
Face Detection (HP)
|
100% |
5456
64.8 IPS |
|
|
Face Detection (Q)
|
97% |
4537
54.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
3971
30.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
5555
42.9 IPS |
|
|
Depth Estimation (Q)
|
63% |
4433
41.6 IPS |
|
|
Style Transfer (SP)
|
100% |
10071
12.9 IPS |
|
|
Style Transfer (HP)
|
100% |
19938
25.6 IPS |
|
|
Style Transfer (Q)
|
98% |
18901
24.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1834
67.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2750
101.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2817
104.4 IPS |
|
|
Text Classification (SP)
|
35% |
46
450.7 IPS |
|
|
Text Classification (HP)
|
35% |
67
612.5 IPS |
|
|
Text Classification (Q)
|
35% |
60
587.9 IPS |
|
|
Machine Translation (SP)
|
100% |
757
13.0 IPS |
|
|
Machine Translation (HP)
|
97% |
841
14.5 IPS |
|
|
Machine Translation (Q)
|
49% |
313
11.8 IPS |
