motorola moto e32(s)
Geekbench AI Score
294
Single Precision Score
288
Half Precision Score
317
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | benched |
| Upload Date | October 08 2024 03:31 PM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM MT6765H |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | motorola moto e32(s) |
| Model ID | motorola moto e32(s) |
| Motherboard | p410ae |
| CPU Information | |
|---|---|
| Name | ARM MT6765H |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3331 revision 4 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.30 GHz |
| Memory Information | |
|---|---|
| Size | 3.68 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
149
27.8 IPS |
|
|
Image Classification (HP)
|
100% |
135
25.1 IPS |
|
|
Image Classification (Q)
|
100% |
223
41.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
206
3.34 IPS |
|
|
Image Segmentation (HP)
|
100% |
204
3.30 IPS |
|
|
Image Segmentation (Q)
|
98% |
337
5.49 IPS |
|
|
Pose Estimation (SP)
|
100% |
749
0.87 IPS |
|
|
Pose Estimation (HP)
|
100% |
692
0.81 IPS |
|
|
Pose Estimation (Q)
|
84% |
559
0.66 IPS |
|
|
Object Detection (SP)
|
100% |
152
12.0 IPS |
|
|
Object Detection (HP)
|
100% |
151
12.0 IPS |
|
|
Object Detection (Q)
|
83% |
215
17.3 IPS |
|
|
Face Detection (SP)
|
100% |
354
4.21 IPS |
|
|
Face Detection (HP)
|
100% |
354
4.21 IPS |
|
|
Face Detection (Q)
|
95% |
637
7.60 IPS |
|
|
Depth Estimation (SP)
|
100% |
477
3.68 IPS |
|
|
Depth Estimation (HP)
|
99% |
460
3.54 IPS |
|
|
Depth Estimation (Q)
|
64% |
546
5.00 IPS |
|
|
Style Transfer (SP)
|
89% |
1174
1.52 IPS |
|
|
Style Transfer (HP)
|
89% |
1184
1.54 IPS |
|
|
Style Transfer (Q)
|
98% |
1222
1.58 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
227
8.39 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
235
8.66 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
272
10.1 IPS |
|
|
Text Classification (SP)
|
100% |
150
199.9 IPS |
|
|
Text Classification (HP)
|
100% |
150
200.5 IPS |
|
|
Text Classification (Q)
|
88% |
132
178.2 IPS |
|
|
Machine Translation (SP)
|
100% |
205
3.54 IPS |
|
|
Machine Translation (HP)
|
100% |
204
3.52 IPS |
|
|
Machine Translation (Q)
|
50% |
75
2.66 IPS |
