motorola motorola edge 50 neo
Geekbench AI Score
488
Single Precision Score
758
Half Precision Score
603
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | Nickayz |
| Upload Date | March 24 2026 01:17 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | motorola motorola edge 50 neo |
| Model ID | motorola motorola edge 50 neo |
| Motherboard | vienna |
| 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 @ 2.50 GHz |
| Memory Information | |
|---|---|
| Size | 11.17 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
266
49.4 IPS |
|
|
Image Classification (HP)
|
100% |
422
78.5 IPS |
|
|
Image Classification (Q)
|
97% |
468
87.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
540
8.75 IPS |
|
|
Image Segmentation (HP)
|
100% |
954
15.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
876
14.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
2167
2.53 IPS |
|
|
Pose Estimation (HP)
|
100% |
3829
4.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
3555
4.17 IPS |
|
|
Object Detection (SP)
|
100% |
217
17.2 IPS |
|
|
Object Detection (HP)
|
99% |
351
27.8 IPS |
|
|
Object Detection (Q)
|
83% |
329
26.6 IPS |
|
|
Face Detection (SP)
|
100% |
1005
11.9 IPS |
|
|
Face Detection (HP)
|
100% |
1593
18.9 IPS |
|
|
Face Detection (Q)
|
96% |
1388
16.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
1235
9.52 IPS |
|
|
Depth Estimation (HP)
|
98% |
2036
15.7 IPS |
|
|
Depth Estimation (Q)
|
62% |
1634
15.5 IPS |
|
|
Style Transfer (SP)
|
100% |
3604
4.63 IPS |
|
|
Style Transfer (HP)
|
100% |
6443
8.28 IPS |
|
|
Style Transfer (Q)
|
98% |
6315
8.14 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
660
24.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1293
47.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1058
39.2 IPS |
|
|
Text Classification (SP)
|
35% |
12
108.3 IPS |
|
|
Text Classification (HP)
|
29% |
11
189.9 IPS |
|
|
Text Classification (Q)
|
32% |
9
122.2 IPS |
|
|
Machine Translation (SP)
|
100% |
323
5.56 IPS |
|
|
Machine Translation (HP)
|
100% |
393
6.78 IPS |
|
|
Machine Translation (Q)
|
43% |
98
5.70 IPS |
