samsung SM-A235F
Geekbench ML Score
257
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 15 2024 01:39 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A235F |
| Model ID | samsung SM-A235F |
| Motherboard | bengal |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3337 revision 0 |
| Base Frequency | 1.90 GHz |
| Cluster 1 | 4 Cores @ 1.90 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 5.45 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
137
25.7 IPS |
|
|
Image Classification (F16)
|
100% |
141
26.4 IPS |
|
|
Image Classification (I8)
|
97% |
222
41.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
189
3.16 IPS |
|
|
Image Segmentation (F16)
|
100% |
193
3.22 IPS |
|
|
Image Segmentation (I8)
|
98% |
235
3.93 IPS |
|
|
Pose Estimation (F32)
|
100% |
241
0.29 IPS |
|
|
Pose Estimation (F16)
|
100% |
249
0.30 IPS |
|
|
Pose Estimation (I8)
|
100% |
745
0.90 IPS |
|
|
Object Detection (F32)
|
100% |
147
11.0 IPS |
|
|
Object Detection (F16)
|
100% |
145
10.8 IPS |
|
|
Object Detection (I8)
|
61% |
259
19.3 IPS |
|
|
Face Detection (F32)
|
100% |
293
3.49 IPS |
|
|
Face Detection (F16)
|
100% |
291
3.46 IPS |
|
|
Face Detection (I8)
|
86% |
517
6.14 IPS |
|
|
Depth Estimation (F32)
|
100% |
273
2.11 IPS |
|
|
Depth Estimation (F16)
|
100% |
267
2.07 IPS |
|
|
Depth Estimation (I8)
|
95% |
532
4.12 IPS |
|
|
Style Transfer (F32)
|
100% |
439
0.58 IPS |
|
|
Style Transfer (F16)
|
100% |
443
0.58 IPS |
|
|
Style Transfer (I8)
|
98% |
1039
1.37 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
163
5.81 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
157
5.61 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
390
13.9 IPS |
|
|
Text Classification (F32)
|
100% |
186
266.8 IPS |
|
|
Text Classification (F16)
|
100% |
185
265.2 IPS |
|
|
Text Classification (I8)
|
92% |
146
210.5 IPS |
|
|
Machine Translation (F32)
|
100% |
315
5.79 IPS |
|
|
Machine Translation (F16)
|
100% |
309
5.69 IPS |
|
|
Machine Translation (I8)
|
64% |
139
2.55 IPS |
