samsung SM-F956U1
Geekbench ML Score
1278
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 27 2024 05:06 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-F956U1 |
| Model ID | samsung SM-F956U1 |
| 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 | 10.86 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
655
122.6 IPS |
|
|
Image Classification (F16)
|
100% |
642
120.1 IPS |
|
|
Image Classification (I8)
|
97% |
1075
201.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
875
14.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
840
14.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
987
16.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
1503
1.82 IPS |
|
|
Pose Estimation (F16)
|
100% |
1429
1.73 IPS |
|
|
Pose Estimation (I8)
|
100% |
6118
7.41 IPS |
|
|
Object Detection (F32)
|
100% |
632
47.2 IPS |
|
|
Object Detection (F16)
|
100% |
650
48.6 IPS |
|
|
Object Detection (I8)
|
61% |
1438
107.3 IPS |
|
|
Face Detection (F32)
|
100% |
1481
17.6 IPS |
|
|
Face Detection (F16)
|
100% |
1468
17.5 IPS |
|
|
Face Detection (I8)
|
86% |
2490
29.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
1456
11.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
1408
10.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
2489
19.3 IPS |
|
|
Style Transfer (F32)
|
100% |
2517
3.31 IPS |
|
|
Style Transfer (F16)
|
100% |
2409
3.17 IPS |
|
|
Style Transfer (I8)
|
98% |
5061
6.66 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
981
35.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
935
33.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2582
92.2 IPS |
|
|
Text Classification (F32)
|
100% |
680
977.2 IPS |
|
|
Text Classification (F16)
|
100% |
668
960.5 IPS |
|
|
Text Classification (I8)
|
92% |
553
795.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1481
27.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1473
27.1 IPS |
|
|
Machine Translation (I8)
|
64% |
572
10.5 IPS |
