samsung SM-A256E
Geekbench ML Score
301
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 18 2024 04:55 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A256E |
| Model ID | samsung SM-A256E |
| Motherboard | s5e8825 |
| 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 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.22 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
169
31.5 IPS |
|
|
Image Classification (F16)
|
100% |
304
56.9 IPS |
|
|
Image Classification (I8)
|
97% |
291
54.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
230
3.85 IPS |
|
|
Image Segmentation (F16)
|
100% |
382
6.37 IPS |
|
|
Image Segmentation (I8)
|
98% |
374
6.25 IPS |
|
|
Pose Estimation (F32)
|
100% |
147
0.18 IPS |
|
|
Pose Estimation (F16)
|
100% |
173
0.21 IPS |
|
|
Pose Estimation (I8)
|
100% |
173
0.21 IPS |
|
|
Object Detection (F32)
|
100% |
143
10.7 IPS |
|
|
Object Detection (F16)
|
100% |
231
17.3 IPS |
|
|
Object Detection (I8)
|
62% |
232
17.3 IPS |
|
|
Face Detection (F32)
|
100% |
557
6.62 IPS |
|
|
Face Detection (F16)
|
98% |
830
9.87 IPS |
|
|
Face Detection (I8)
|
86% |
780
9.27 IPS |
|
|
Depth Estimation (F32)
|
100% |
293
2.27 IPS |
|
|
Depth Estimation (F16)
|
100% |
378
2.93 IPS |
|
|
Depth Estimation (I8)
|
95% |
376
2.92 IPS |
|
|
Style Transfer (F32)
|
100% |
583
0.77 IPS |
|
|
Style Transfer (F16)
|
100% |
822
1.08 IPS |
|
|
Style Transfer (I8)
|
98% |
821
1.08 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
164
5.86 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
253
9.02 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
251
8.97 IPS |
|
|
Text Classification (F32)
|
100% |
157
225.0 IPS |
|
|
Text Classification (F16)
|
100% |
156
224.5 IPS |
|
|
Text Classification (I8)
|
92% |
313
449.8 IPS |
|
|
Machine Translation (F32)
|
100% |
289
5.31 IPS |
|
|
Machine Translation (F16)
|
100% |
287
5.28 IPS |
|
|
Machine Translation (I8)
|
64% |
384
7.07 IPS |
