samsung SM-A155M
Geekbench ML Score
341
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 17 2024 12:19 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A155M |
| Model ID | samsung SM-A155M |
| Motherboard | a15 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.20 GHz |
| Memory Information | |
|---|---|
| Size | 7.48 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
161
30.1 IPS |
|
|
Image Classification (F16)
|
100% |
165
30.9 IPS |
|
|
Image Classification (I8)
|
97% |
268
50.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
251
4.19 IPS |
|
|
Image Segmentation (F16)
|
100% |
245
4.09 IPS |
|
|
Image Segmentation (I8)
|
98% |
331
5.54 IPS |
|
|
Pose Estimation (F32)
|
100% |
351
0.43 IPS |
|
|
Pose Estimation (F16)
|
100% |
358
0.43 IPS |
|
|
Pose Estimation (I8)
|
100% |
1491
1.81 IPS |
|
|
Object Detection (F32)
|
100% |
191
14.2 IPS |
|
|
Object Detection (F16)
|
100% |
191
14.3 IPS |
|
|
Object Detection (I8)
|
61% |
339
25.3 IPS |
|
|
Face Detection (F32)
|
100% |
381
4.52 IPS |
|
|
Face Detection (F16)
|
100% |
387
4.61 IPS |
|
|
Face Detection (I8)
|
86% |
657
7.81 IPS |
|
|
Depth Estimation (F32)
|
100% |
375
2.91 IPS |
|
|
Depth Estimation (F16)
|
100% |
371
2.87 IPS |
|
|
Depth Estimation (I8)
|
95% |
698
5.41 IPS |
|
|
Style Transfer (F32)
|
100% |
606
0.80 IPS |
|
|
Style Transfer (F16)
|
100% |
608
0.80 IPS |
|
|
Style Transfer (I8)
|
98% |
1757
2.31 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
215
7.66 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
216
7.71 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
610
21.8 IPS |
|
|
Text Classification (F32)
|
100% |
197
282.9 IPS |
|
|
Text Classification (F16)
|
100% |
193
277.7 IPS |
|
|
Text Classification (I8)
|
92% |
157
225.6 IPS |
|
|
Machine Translation (F32)
|
100% |
377
6.95 IPS |
|
|
Machine Translation (F16)
|
100% |
374
6.88 IPS |
|
|
Machine Translation (I8)
|
64% |
211
3.88 IPS |
