motorola motorola razr 2023
Geekbench ML Score
380
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 01:43 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | motorola motorola razr 2023 |
| Model ID | motorola motorola razr 2023 |
| Motherboard | lynkco |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3399 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.36 GHz |
| Cluster 3 | 1 Core @ 2.52 GHz |
| Memory Information | |
|---|---|
| Size | 7.19 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
223
41.8 IPS |
|
|
Image Classification (F16)
|
100% |
372
69.6 IPS |
|
|
Image Classification (I8)
|
97% |
347
65.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
354
5.92 IPS |
|
|
Image Segmentation (F16)
|
100% |
496
8.29 IPS |
|
|
Image Segmentation (I8)
|
98% |
502
8.39 IPS |
|
|
Pose Estimation (F32)
|
100% |
375
0.45 IPS |
|
|
Pose Estimation (F16)
|
100% |
179
0.22 IPS |
|
|
Pose Estimation (I8)
|
100% |
177
0.21 IPS |
|
|
Object Detection (F32)
|
100% |
193
14.4 IPS |
|
|
Object Detection (F16)
|
100% |
245
18.3 IPS |
|
|
Object Detection (I8)
|
62% |
259
19.3 IPS |
|
|
Face Detection (F32)
|
100% |
718
8.54 IPS |
|
|
Face Detection (F16)
|
97% |
1048
12.5 IPS |
|
|
Face Detection (I8)
|
87% |
971
11.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
535
4.15 IPS |
|
|
Depth Estimation (F16)
|
100% |
747
5.80 IPS |
|
|
Depth Estimation (I8)
|
95% |
743
5.76 IPS |
|
|
Style Transfer (F32)
|
100% |
1122
1.48 IPS |
|
|
Style Transfer (F16)
|
100% |
1915
2.52 IPS |
|
|
Style Transfer (I8)
|
98% |
1922
2.53 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
256
9.13 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
264
9.41 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
261
9.33 IPS |
|
|
Text Classification (F32)
|
100% |
82
117.6 IPS |
|
|
Text Classification (F16)
|
100% |
123
177.5 IPS |
|
|
Text Classification (I8)
|
92% |
234
336.8 IPS |
|
|
Machine Translation (F32)
|
100% |
233
4.29 IPS |
|
|
Machine Translation (F16)
|
100% |
252
4.64 IPS |
|
|
Machine Translation (I8)
|
64% |
325
5.98 IPS |
