samsung SM-S928U1
Geekbench ML Score
1272
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 16 2024 11:16 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S928U1 |
| Model ID | samsung SM-S928U1 |
| 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% |
617
115.5 IPS |
|
|
Image Classification (F16)
|
100% |
637
119.2 IPS |
|
|
Image Classification (I8)
|
97% |
1112
208.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
822
13.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
828
13.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
974
16.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
1477
1.79 IPS |
|
|
Pose Estimation (F16)
|
100% |
1398
1.69 IPS |
|
|
Pose Estimation (I8)
|
100% |
5913
7.16 IPS |
|
|
Object Detection (F32)
|
100% |
615
45.9 IPS |
|
|
Object Detection (F16)
|
100% |
625
46.7 IPS |
|
|
Object Detection (I8)
|
61% |
1421
106.1 IPS |
|
|
Face Detection (F32)
|
100% |
1473
17.5 IPS |
|
|
Face Detection (F16)
|
100% |
1387
16.5 IPS |
|
|
Face Detection (I8)
|
86% |
2110
25.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
1265
9.81 IPS |
|
|
Depth Estimation (F16)
|
100% |
1361
10.6 IPS |
|
|
Depth Estimation (I8)
|
95% |
2694
20.9 IPS |
|
|
Style Transfer (F32)
|
100% |
2463
3.24 IPS |
|
|
Style Transfer (F16)
|
100% |
2485
3.27 IPS |
|
|
Style Transfer (I8)
|
98% |
5187
6.82 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1013
36.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
958
34.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2842
101.5 IPS |
|
|
Text Classification (F32)
|
100% |
750
1.08 KIPS |
|
|
Text Classification (F16)
|
100% |
760
1.09 KIPS |
|
|
Text Classification (I8)
|
92% |
508
729.4 IPS |
|
|
Machine Translation (F32)
|
100% |
1584
29.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1500
27.6 IPS |
|
|
Machine Translation (I8)
|
64% |
597
11.0 IPS |
