motorola motorola edge 60 fusion
Geekbench AI Score
843
Single Precision Score
846
Half Precision Score
1984
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | August 20 2025 06:59 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | motorola motorola edge 60 fusion |
| Model ID | motorola motorola edge 60 fusion |
| Motherboard | scout |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 4 Cores @ 2.60 GHz |
| Memory Information | |
|---|---|
| Size | 7.25 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
438
81.4 IPS |
|
|
Image Classification (HP)
|
100% |
422
78.4 IPS |
|
|
Image Classification (Q)
|
100% |
1424
264.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
504
8.17 IPS |
|
|
Image Segmentation (HP)
|
100% |
516
8.36 IPS |
|
|
Image Segmentation (Q)
|
98% |
1688
27.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
1815
2.12 IPS |
|
|
Pose Estimation (HP)
|
100% |
1864
2.17 IPS |
|
|
Pose Estimation (Q)
|
84% |
3756
4.45 IPS |
|
|
Object Detection (SP)
|
100% |
441
35.0 IPS |
|
|
Object Detection (HP)
|
100% |
436
34.6 IPS |
|
|
Object Detection (Q)
|
83% |
1389
112.2 IPS |
|
|
Face Detection (SP)
|
100% |
926
11.0 IPS |
|
|
Face Detection (HP)
|
100% |
982
11.7 IPS |
|
|
Face Detection (Q)
|
95% |
3318
39.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
1361
10.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
1378
10.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
3424
31.4 IPS |
|
|
Style Transfer (SP)
|
89% |
3350
4.35 IPS |
|
|
Style Transfer (HP)
|
89% |
3376
4.38 IPS |
|
|
Style Transfer (Q)
|
98% |
8431
10.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
716
26.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
734
27.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2023
75.0 IPS |
|
|
Text Classification (SP)
|
100% |
500
667.1 IPS |
|
|
Text Classification (HP)
|
100% |
478
637.7 IPS |
|
|
Text Classification (Q)
|
88% |
934
1.26 KIPS |
|
|
Machine Translation (SP)
|
100% |
685
11.8 IPS |
|
|
Machine Translation (HP)
|
100% |
669
11.5 IPS |
|
|
Machine Translation (Q)
|
50% |
417
14.8 IPS |
