samsung SM-A366U
Geekbench ML Score
527
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 22 2025 04:11 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-A366U |
| Model ID | samsung SM-A366U |
| Motherboard | parrot |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 2 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 5.16 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
239
44.7 IPS |
|
|
Image Classification (F16)
|
100% |
236
44.1 IPS |
|
|
Image Classification (I8)
|
97% |
604
113.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
304
5.07 IPS |
|
|
Image Segmentation (F16)
|
100% |
342
5.71 IPS |
|
|
Image Segmentation (I8)
|
98% |
528
8.82 IPS |
|
|
Pose Estimation (F32)
|
100% |
512
0.62 IPS |
|
|
Pose Estimation (F16)
|
100% |
517
0.63 IPS |
|
|
Pose Estimation (I8)
|
100% |
2008
2.43 IPS |
|
|
Object Detection (F32)
|
100% |
242
18.1 IPS |
|
|
Object Detection (F16)
|
100% |
260
19.4 IPS |
|
|
Object Detection (I8)
|
61% |
677
50.6 IPS |
|
|
Face Detection (F32)
|
100% |
520
6.19 IPS |
|
|
Face Detection (F16)
|
100% |
512
6.09 IPS |
|
|
Face Detection (I8)
|
86% |
1400
16.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
552
4.28 IPS |
|
|
Depth Estimation (F16)
|
100% |
549
4.25 IPS |
|
|
Depth Estimation (I8)
|
95% |
1408
10.9 IPS |
|
|
Style Transfer (F32)
|
100% |
877
1.15 IPS |
|
|
Style Transfer (F16)
|
100% |
885
1.16 IPS |
|
|
Style Transfer (I8)
|
98% |
2438
3.21 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
307
10.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
321
11.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1061
37.9 IPS |
|
|
Text Classification (F32)
|
100% |
331
476.0 IPS |
|
|
Text Classification (F16)
|
100% |
321
461.1 IPS |
|
|
Text Classification (I8)
|
92% |
302
433.8 IPS |
|
|
Machine Translation (F32)
|
100% |
572
10.5 IPS |
|
|
Machine Translation (F16)
|
100% |
586
10.8 IPS |
|
|
Machine Translation (I8)
|
64% |
332
6.11 IPS |
