Samsung Galaxy A73
Geekbench ML Score
287
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 16 2024 09:55 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
124
23.1 IPS |
|
|
Image Classification (F16)
|
100% |
124
23.2 IPS |
|
|
Image Classification (I8)
|
97% |
340
63.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
164
2.73 IPS |
|
|
Image Segmentation (F16)
|
100% |
164
2.73 IPS |
|
|
Image Segmentation (I8)
|
98% |
365
6.09 IPS |
|
|
Pose Estimation (F32)
|
100% |
220
0.27 IPS |
|
|
Pose Estimation (F16)
|
100% |
219
0.27 IPS |
|
|
Pose Estimation (I8)
|
100% |
834
1.01 IPS |
|
|
Object Detection (F32)
|
100% |
130
9.67 IPS |
|
|
Object Detection (F16)
|
100% |
130
9.67 IPS |
|
|
Object Detection (I8)
|
61% |
371
27.7 IPS |
|
|
Face Detection (F32)
|
100% |
317
3.77 IPS |
|
|
Face Detection (F16)
|
100% |
317
3.77 IPS |
|
|
Face Detection (I8)
|
86% |
749
8.91 IPS |
|
|
Depth Estimation (F32)
|
100% |
277
2.15 IPS |
|
|
Depth Estimation (F16)
|
100% |
277
2.15 IPS |
|
|
Depth Estimation (I8)
|
95% |
808
6.27 IPS |
|
|
Style Transfer (F32)
|
100% |
471
0.62 IPS |
|
|
Style Transfer (F16)
|
100% |
471
0.62 IPS |
|
|
Style Transfer (I8)
|
98% |
1299
1.71 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
142
5.07 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
142
5.08 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
502
17.9 IPS |
|
|
Text Classification (F32)
|
100% |
167
240.7 IPS |
|
|
Text Classification (F16)
|
100% |
168
240.8 IPS |
|
|
Text Classification (I8)
|
92% |
322
462.2 IPS |
|
|
Machine Translation (F32)
|
100% |
300
5.52 IPS |
|
|
Machine Translation (F16)
|
100% |
299
5.50 IPS |
|
|
Machine Translation (I8)
|
64% |
391
7.19 IPS |
