motorola motorola edge 70
Geekbench AI Score
1000
Single Precision Score
1700
Half Precision Score
1315
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 06 2025 08:56 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | motorola motorola edge 70 |
| Model ID | motorola motorola edge 70 |
| Motherboard | roadstr |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3457 revision 1 |
| Base Frequency | 1.84 GHz |
| Cluster 1 | 3 Cores @ 1.84 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Cluster 3 | 1 Core @ 2.80 GHz |
| Memory Information | |
|---|---|
| Size | 11.04 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
761
141.5 IPS |
|
|
Image Classification (HP)
|
100% |
1151
214.0 IPS |
|
|
Image Classification (Q)
|
100% |
1037
192.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1205
19.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
1967
31.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
1967
32.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
4508
5.26 IPS |
|
|
Pose Estimation (HP)
|
99% |
8401
9.83 IPS |
|
|
Pose Estimation (Q)
|
96% |
8113
9.51 IPS |
|
|
Object Detection (SP)
|
100% |
525
41.7 IPS |
|
|
Object Detection (HP)
|
99% |
953
75.6 IPS |
|
|
Object Detection (Q)
|
87% |
1081
86.8 IPS |
|
|
Face Detection (SP)
|
100% |
1680
20.0 IPS |
|
|
Face Detection (HP)
|
100% |
2991
35.5 IPS |
|
|
Face Detection (Q)
|
97% |
2420
28.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
2598
20.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
4703
36.3 IPS |
|
|
Depth Estimation (Q)
|
61% |
3543
34.9 IPS |
|
|
Style Transfer (SP)
|
100% |
5257
6.76 IPS |
|
|
Style Transfer (HP)
|
100% |
10413
13.4 IPS |
|
|
Style Transfer (Q)
|
98% |
10188
13.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1001
36.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1864
68.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1674
62.0 IPS |
|
|
Text Classification (SP)
|
35% |
38
370.6 IPS |
|
|
Text Classification (HP)
|
35% |
60
543.9 IPS |
|
|
Text Classification (Q)
|
33% |
43
521.9 IPS |
|
|
Machine Translation (SP)
|
100% |
529
9.12 IPS |
|
|
Machine Translation (HP)
|
97% |
679
11.7 IPS |
|
|
Machine Translation (Q)
|
43% |
138
7.83 IPS |
