samsung SM-S928B
Geekbench ML Score
1242
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 27 2024 11:18 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S928B |
| Model ID | samsung SM-S928B |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 10.81 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
588
110.0 IPS |
|
|
Image Classification (F16)
|
100% |
582
108.9 IPS |
|
|
Image Classification (I8)
|
97% |
1029
192.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
787
13.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
798
13.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
932
15.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
1425
1.73 IPS |
|
|
Pose Estimation (F16)
|
100% |
1374
1.66 IPS |
|
|
Pose Estimation (I8)
|
100% |
5837
7.07 IPS |
|
|
Object Detection (F32)
|
100% |
596
44.5 IPS |
|
|
Object Detection (F16)
|
100% |
606
45.3 IPS |
|
|
Object Detection (I8)
|
61% |
1283
95.8 IPS |
|
|
Face Detection (F32)
|
100% |
1389
16.5 IPS |
|
|
Face Detection (F16)
|
100% |
1308
15.6 IPS |
|
|
Face Detection (I8)
|
86% |
2481
29.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1374
10.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
1361
10.6 IPS |
|
|
Depth Estimation (I8)
|
95% |
2670
20.7 IPS |
|
|
Style Transfer (F32)
|
100% |
2342
3.08 IPS |
|
|
Style Transfer (F16)
|
100% |
2430
3.20 IPS |
|
|
Style Transfer (I8)
|
98% |
5065
6.66 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1033
36.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1011
36.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2758
98.5 IPS |
|
|
Text Classification (F32)
|
100% |
726
1.04 KIPS |
|
|
Text Classification (F16)
|
100% |
716
1.03 KIPS |
|
|
Text Classification (I8)
|
92% |
515
740.4 IPS |
|
|
Machine Translation (F32)
|
100% |
1478
27.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1385
25.5 IPS |
|
|
Machine Translation (I8)
|
64% |
610
11.2 IPS |
