samsung SM-A356B
Geekbench ML Score
347
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | kszycho |
| Upload Date | September 18 2024 12:14 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A356B |
| Model ID | samsung SM-A356B |
| Motherboard | s5e8835 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.26 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
210
39.3 IPS |
|
|
Image Classification (F16)
|
100% |
255
47.7 IPS |
|
|
Image Classification (I8)
|
97% |
351
65.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
269
4.50 IPS |
|
|
Image Segmentation (F16)
|
100% |
438
7.32 IPS |
|
|
Image Segmentation (I8)
|
98% |
417
6.97 IPS |
|
|
Pose Estimation (F32)
|
100% |
183
0.22 IPS |
|
|
Pose Estimation (F16)
|
100% |
217
0.26 IPS |
|
|
Pose Estimation (I8)
|
100% |
217
0.26 IPS |
|
|
Object Detection (F32)
|
100% |
169
12.6 IPS |
|
|
Object Detection (F16)
|
100% |
260
19.4 IPS |
|
|
Object Detection (I8)
|
62% |
264
19.7 IPS |
|
|
Face Detection (F32)
|
100% |
664
7.90 IPS |
|
|
Face Detection (F16)
|
98% |
986
11.7 IPS |
|
|
Face Detection (I8)
|
86% |
902
10.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
363
2.82 IPS |
|
|
Depth Estimation (F16)
|
100% |
474
3.68 IPS |
|
|
Depth Estimation (I8)
|
95% |
470
3.64 IPS |
|
|
Style Transfer (F32)
|
100% |
720
0.95 IPS |
|
|
Style Transfer (F16)
|
100% |
1024
1.35 IPS |
|
|
Style Transfer (I8)
|
98% |
1026
1.35 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
192
6.84 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
283
10.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
276
9.85 IPS |
|
|
Text Classification (F32)
|
100% |
168
241.2 IPS |
|
|
Text Classification (F16)
|
100% |
168
241.3 IPS |
|
|
Text Classification (I8)
|
92% |
323
464.7 IPS |
|
|
Machine Translation (F32)
|
100% |
305
5.61 IPS |
|
|
Machine Translation (F16)
|
100% |
304
5.60 IPS |
|
|
Machine Translation (I8)
|
64% |
395
7.27 IPS |
