samsung SM-A5460
Geekbench ML Score
379
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 09 2024 10:19 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A5460 |
| Model ID | samsung SM-A5460 |
| 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
169
31.7 IPS |
|
|
Image Classification (F16)
|
100% |
226
42.3 IPS |
|
|
Image Classification (I8)
|
97% |
648
121.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
245
4.09 IPS |
|
|
Image Segmentation (F16)
|
100% |
211
3.53 IPS |
|
|
Image Segmentation (I8)
|
98% |
304
5.08 IPS |
|
|
Pose Estimation (F32)
|
100% |
459
0.56 IPS |
|
|
Pose Estimation (F16)
|
100% |
452
0.55 IPS |
|
|
Pose Estimation (I8)
|
100% |
2276
2.76 IPS |
|
|
Object Detection (F32)
|
100% |
273
20.4 IPS |
|
|
Object Detection (F16)
|
100% |
224
16.7 IPS |
|
|
Object Detection (I8)
|
61% |
743
55.5 IPS |
|
|
Face Detection (F32)
|
100% |
314
3.73 IPS |
|
|
Face Detection (F16)
|
100% |
316
3.76 IPS |
|
|
Face Detection (I8)
|
86% |
529
6.30 IPS |
|
|
Depth Estimation (F32)
|
100% |
375
2.91 IPS |
|
|
Depth Estimation (F16)
|
100% |
377
2.93 IPS |
|
|
Depth Estimation (I8)
|
95% |
450
3.49 IPS |
|
|
Style Transfer (F32)
|
100% |
776
1.02 IPS |
|
|
Style Transfer (F16)
|
100% |
799
1.05 IPS |
|
|
Style Transfer (I8)
|
98% |
2103
2.77 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
274
9.79 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
232
8.27 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
792
28.3 IPS |
|
|
Text Classification (F32)
|
100% |
386
554.9 IPS |
|
|
Text Classification (F16)
|
100% |
330
474.1 IPS |
|
|
Text Classification (I8)
|
92% |
275
395.8 IPS |
|
|
Machine Translation (F32)
|
100% |
178
3.27 IPS |
|
|
Machine Translation (F16)
|
100% |
241
4.44 IPS |
|
|
Machine Translation (I8)
|
64% |
88
1.62 IPS |
