samsung SM-F956U1
Geekbench ML Score
635
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 11 2024 09:18 PM |
| Views | 1 |
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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
307
57.4 IPS |
|
|
Image Classification (F16)
|
100% |
292
54.6 IPS |
|
|
Image Classification (I8)
|
97% |
773
144.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
355
5.93 IPS |
|
|
Image Segmentation (F16)
|
100% |
352
5.88 IPS |
|
|
Image Segmentation (I8)
|
98% |
744
12.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
474
0.57 IPS |
|
|
Pose Estimation (F16)
|
100% |
468
0.57 IPS |
|
|
Pose Estimation (I8)
|
100% |
1911
2.31 IPS |
|
|
Object Detection (F32)
|
100% |
301
22.4 IPS |
|
|
Object Detection (F16)
|
100% |
299
22.3 IPS |
|
|
Object Detection (I8)
|
61% |
826
61.7 IPS |
|
|
Face Detection (F32)
|
100% |
695
8.26 IPS |
|
|
Face Detection (F16)
|
100% |
680
8.09 IPS |
|
|
Face Detection (I8)
|
86% |
1592
18.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
595
4.61 IPS |
|
|
Depth Estimation (F16)
|
100% |
588
4.56 IPS |
|
|
Depth Estimation (I8)
|
95% |
1733
13.4 IPS |
|
|
Style Transfer (F32)
|
100% |
964
1.27 IPS |
|
|
Style Transfer (F16)
|
100% |
957
1.26 IPS |
|
|
Style Transfer (I8)
|
98% |
2410
3.17 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
340
12.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
348
12.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1180
42.1 IPS |
|
|
Text Classification (F32)
|
100% |
415
596.3 IPS |
|
|
Text Classification (F16)
|
100% |
420
603.1 IPS |
|
|
Text Classification (I8)
|
92% |
693
996.5 IPS |
|
|
Machine Translation (F32)
|
100% |
686
12.6 IPS |
|
|
Machine Translation (F16)
|
100% |
659
12.1 IPS |
|
|
Machine Translation (I8)
|
64% |
778
14.3 IPS |
