samsung SM-S928B
Geekbench ML Score
1048
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 01 2024 07:07 PM |
| Views | 2 |
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% |
473
88.6 IPS |
|
|
Image Classification (F16)
|
100% |
469
87.7 IPS |
|
|
Image Classification (I8)
|
97% |
830
155.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
636
10.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
634
10.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
723
12.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
1360
1.65 IPS |
|
|
Pose Estimation (F16)
|
100% |
1341
1.62 IPS |
|
|
Pose Estimation (I8)
|
100% |
4915
5.95 IPS |
|
|
Object Detection (F32)
|
100% |
473
35.3 IPS |
|
|
Object Detection (F16)
|
100% |
493
36.8 IPS |
|
|
Object Detection (I8)
|
61% |
915
68.3 IPS |
|
|
Face Detection (F32)
|
100% |
1126
13.4 IPS |
|
|
Face Detection (F16)
|
100% |
1137
13.5 IPS |
|
|
Face Detection (I8)
|
86% |
2082
24.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
1214
9.41 IPS |
|
|
Depth Estimation (F16)
|
100% |
1198
9.29 IPS |
|
|
Depth Estimation (I8)
|
95% |
2102
16.3 IPS |
|
|
Style Transfer (F32)
|
100% |
2368
3.11 IPS |
|
|
Style Transfer (F16)
|
100% |
2333
3.07 IPS |
|
|
Style Transfer (I8)
|
98% |
5037
6.63 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
857
30.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
842
30.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2155
77.0 IPS |
|
|
Text Classification (F32)
|
100% |
570
818.8 IPS |
|
|
Text Classification (F16)
|
100% |
580
833.7 IPS |
|
|
Text Classification (I8)
|
92% |
419
601.8 IPS |
|
|
Machine Translation (F32)
|
100% |
1268
23.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1245
22.9 IPS |
|
|
Machine Translation (I8)
|
64% |
516
9.50 IPS |
