samsung SM-A155M
Geekbench ML Score
351
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 17 2024 12:26 AM |
| Views | 4 |
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% |
160
30.0 IPS |
|
|
Image Classification (F16)
|
100% |
163
30.5 IPS |
|
|
Image Classification (I8)
|
97% |
286
53.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
243
4.05 IPS |
|
|
Image Segmentation (F16)
|
100% |
255
4.25 IPS |
|
|
Image Segmentation (I8)
|
98% |
354
5.91 IPS |
|
|
Pose Estimation (F32)
|
100% |
366
0.44 IPS |
|
|
Pose Estimation (F16)
|
100% |
364
0.44 IPS |
|
|
Pose Estimation (I8)
|
100% |
1562
1.89 IPS |
|
|
Object Detection (F32)
|
100% |
199
14.9 IPS |
|
|
Object Detection (F16)
|
100% |
195
14.6 IPS |
|
|
Object Detection (I8)
|
61% |
362
27.0 IPS |
|
|
Face Detection (F32)
|
100% |
391
4.65 IPS |
|
|
Face Detection (F16)
|
100% |
386
4.59 IPS |
|
|
Face Detection (I8)
|
86% |
690
8.20 IPS |
|
|
Depth Estimation (F32)
|
100% |
385
2.99 IPS |
|
|
Depth Estimation (F16)
|
100% |
379
2.94 IPS |
|
|
Depth Estimation (I8)
|
95% |
744
5.77 IPS |
|
|
Style Transfer (F32)
|
100% |
617
0.81 IPS |
|
|
Style Transfer (F16)
|
100% |
620
0.82 IPS |
|
|
Style Transfer (I8)
|
98% |
1826
2.40 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
210
7.49 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
220
7.84 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
635
22.7 IPS |
|
|
Text Classification (F32)
|
100% |
202
290.6 IPS |
|
|
Text Classification (F16)
|
100% |
200
286.8 IPS |
|
|
Text Classification (I8)
|
92% |
158
227.2 IPS |
|
|
Machine Translation (F32)
|
100% |
386
7.10 IPS |
|
|
Machine Translation (F16)
|
100% |
392
7.21 IPS |
|
|
Machine Translation (I8)
|
64% |
228
4.19 IPS |
