Samsung Galaxy A73
Geekbench ML Score
534
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 06 2024 10:16 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Samsung Galaxy A73 |
| Model ID | samsung SM-A736B |
| Motherboard | lahaina |
| 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 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.16 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
247
46.3 IPS |
|
|
Image Classification (F16)
|
100% |
256
48.0 IPS |
|
|
Image Classification (I8)
|
97% |
627
117.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
326
5.44 IPS |
|
|
Image Segmentation (F16)
|
100% |
350
5.84 IPS |
|
|
Image Segmentation (I8)
|
98% |
437
7.29 IPS |
|
|
Pose Estimation (F32)
|
100% |
502
0.61 IPS |
|
|
Pose Estimation (F16)
|
100% |
505
0.61 IPS |
|
|
Pose Estimation (I8)
|
100% |
2800
3.39 IPS |
|
|
Object Detection (F32)
|
100% |
278
20.7 IPS |
|
|
Object Detection (F16)
|
100% |
259
19.4 IPS |
|
|
Object Detection (I8)
|
61% |
734
54.8 IPS |
|
|
Face Detection (F32)
|
100% |
516
6.14 IPS |
|
|
Face Detection (F16)
|
100% |
505
6.01 IPS |
|
|
Face Detection (I8)
|
86% |
1371
16.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
542
4.21 IPS |
|
|
Depth Estimation (F16)
|
100% |
520
4.03 IPS |
|
|
Depth Estimation (I8)
|
95% |
1356
10.5 IPS |
|
|
Style Transfer (F32)
|
100% |
886
1.17 IPS |
|
|
Style Transfer (F16)
|
100% |
885
1.16 IPS |
|
|
Style Transfer (I8)
|
98% |
2451
3.22 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
325
11.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
338
12.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1093
39.1 IPS |
|
|
Text Classification (F32)
|
100% |
335
481.5 IPS |
|
|
Text Classification (F16)
|
100% |
343
492.5 IPS |
|
|
Text Classification (I8)
|
92% |
313
449.4 IPS |
|
|
Machine Translation (F32)
|
100% |
568
10.5 IPS |
|
|
Machine Translation (F16)
|
100% |
548
10.1 IPS |
|
|
Machine Translation (I8)
|
64% |
263
4.84 IPS |
