motorola motorola edge 40
Geekbench ML Score
443
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 03 2024 02:51 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | motorola motorola edge 40 |
| Model ID | motorola motorola edge 40 |
| Motherboard | lyriq |
| CPU Information | |
|---|---|
| Name | ARM MT6891Z_Z/CZA |
| 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 | 7.29 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
277
51.8 IPS |
|
|
Image Classification (F16)
|
100% |
227
42.5 IPS |
|
|
Image Classification (I8)
|
97% |
395
73.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
284
4.75 IPS |
|
|
Image Segmentation (F16)
|
100% |
280
4.68 IPS |
|
|
Image Segmentation (I8)
|
98% |
428
7.15 IPS |
|
|
Pose Estimation (F32)
|
100% |
521
0.63 IPS |
|
|
Pose Estimation (F16)
|
100% |
525
0.64 IPS |
|
|
Pose Estimation (I8)
|
100% |
2187
2.65 IPS |
|
|
Object Detection (F32)
|
100% |
212
15.8 IPS |
|
|
Object Detection (F16)
|
100% |
211
15.8 IPS |
|
|
Object Detection (I8)
|
61% |
421
31.4 IPS |
|
|
Face Detection (F32)
|
100% |
509
6.05 IPS |
|
|
Face Detection (F16)
|
100% |
513
6.11 IPS |
|
|
Face Detection (I8)
|
86% |
1080
12.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
538
4.17 IPS |
|
|
Depth Estimation (F16)
|
100% |
537
4.17 IPS |
|
|
Depth Estimation (I8)
|
95% |
420
3.26 IPS |
|
|
Style Transfer (F32)
|
100% |
955
1.26 IPS |
|
|
Style Transfer (F16)
|
100% |
950
1.25 IPS |
|
|
Style Transfer (I8)
|
98% |
1970
2.59 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
304
10.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
316
11.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
714
25.5 IPS |
|
|
Text Classification (F32)
|
100% |
236
338.7 IPS |
|
|
Text Classification (F16)
|
100% |
239
343.8 IPS |
|
|
Text Classification (I8)
|
92% |
280
402.9 IPS |
|
|
Machine Translation (F32)
|
100% |
545
10.0 IPS |
|
|
Machine Translation (F16)
|
100% |
544
10.0 IPS |
|
|
Machine Translation (I8)
|
64% |
140
2.59 IPS |
