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 03:53 PM |
| Views | 1 |
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% |
235
44.0 IPS |
|
|
Image Classification (F16)
|
100% |
243
45.5 IPS |
|
|
Image Classification (I8)
|
97% |
610
114.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
343
5.72 IPS |
|
|
Image Segmentation (F16)
|
100% |
341
5.69 IPS |
|
|
Image Segmentation (I8)
|
98% |
527
8.80 IPS |
|
|
Pose Estimation (F32)
|
100% |
486
0.59 IPS |
|
|
Pose Estimation (F16)
|
100% |
491
0.60 IPS |
|
|
Pose Estimation (I8)
|
100% |
2105
2.55 IPS |
|
|
Object Detection (F32)
|
100% |
254
18.9 IPS |
|
|
Object Detection (F16)
|
100% |
256
19.1 IPS |
|
|
Object Detection (I8)
|
61% |
673
50.3 IPS |
|
|
Face Detection (F32)
|
100% |
519
6.17 IPS |
|
|
Face Detection (F16)
|
100% |
524
6.22 IPS |
|
|
Face Detection (I8)
|
86% |
1390
16.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
541
4.19 IPS |
|
|
Depth Estimation (F16)
|
100% |
534
4.14 IPS |
|
|
Depth Estimation (I8)
|
95% |
1361
10.6 IPS |
|
|
Style Transfer (F32)
|
100% |
893
1.18 IPS |
|
|
Style Transfer (F16)
|
100% |
868
1.14 IPS |
|
|
Style Transfer (I8)
|
98% |
2516
3.31 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
319
11.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
312
11.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1108
39.6 IPS |
|
|
Text Classification (F32)
|
100% |
322
463.1 IPS |
|
|
Text Classification (F16)
|
100% |
323
464.9 IPS |
|
|
Text Classification (I8)
|
92% |
289
414.9 IPS |
|
|
Machine Translation (F32)
|
100% |
590
10.9 IPS |
|
|
Machine Translation (F16)
|
100% |
536
9.86 IPS |
|
|
Machine Translation (I8)
|
64% |
330
6.08 IPS |
