motorola moto g84 5G
Geekbench ML Score
375
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 13 2024 09:23 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | motorola moto g84 5G |
| Model ID | motorola moto g84 5G |
| Motherboard | bangkk |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 11.24 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
149
27.9 IPS |
|
|
Image Classification (F16)
|
100% |
161
30.1 IPS |
|
|
Image Classification (I8)
|
97% |
367
68.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
251
4.19 IPS |
|
|
Image Segmentation (F16)
|
100% |
248
4.15 IPS |
|
|
Image Segmentation (I8)
|
98% |
411
6.86 IPS |
|
|
Pose Estimation (F32)
|
100% |
347
0.42 IPS |
|
|
Pose Estimation (F16)
|
100% |
367
0.44 IPS |
|
|
Pose Estimation (I8)
|
100% |
1808
2.19 IPS |
|
|
Object Detection (F32)
|
100% |
173
13.0 IPS |
|
|
Object Detection (F16)
|
100% |
173
12.9 IPS |
|
|
Object Detection (I8)
|
61% |
445
33.2 IPS |
|
|
Face Detection (F32)
|
100% |
384
4.57 IPS |
|
|
Face Detection (F16)
|
100% |
371
4.41 IPS |
|
|
Face Detection (I8)
|
86% |
952
11.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
395
3.06 IPS |
|
|
Depth Estimation (F16)
|
100% |
387
3.00 IPS |
|
|
Depth Estimation (I8)
|
95% |
930
7.22 IPS |
|
|
Style Transfer (F32)
|
100% |
712
0.94 IPS |
|
|
Style Transfer (F16)
|
100% |
703
0.92 IPS |
|
|
Style Transfer (I8)
|
98% |
1971
2.59 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
237
8.45 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
257
9.19 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
794
28.4 IPS |
|
|
Text Classification (F32)
|
100% |
222
318.5 IPS |
|
|
Text Classification (F16)
|
100% |
201
288.3 IPS |
|
|
Text Classification (I8)
|
92% |
234
336.1 IPS |
|
|
Machine Translation (F32)
|
100% |
360
6.62 IPS |
|
|
Machine Translation (F16)
|
100% |
371
6.83 IPS |
|
|
Machine Translation (I8)
|
64% |
202
3.73 IPS |
