samsung SM-F956U1
Geekbench ML Score
1147
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 27 2024 05:18 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% |
645
120.7 IPS |
|
|
Image Classification (F16)
|
100% |
622
116.3 IPS |
|
|
Image Classification (I8)
|
97% |
1077
201.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
836
14.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
834
13.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
1040
17.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
1382
1.67 IPS |
|
|
Pose Estimation (F16)
|
100% |
1345
1.63 IPS |
|
|
Pose Estimation (I8)
|
100% |
5867
7.10 IPS |
|
|
Object Detection (F32)
|
100% |
515
38.4 IPS |
|
|
Object Detection (F16)
|
100% |
528
39.4 IPS |
|
|
Object Detection (I8)
|
61% |
1074
80.2 IPS |
|
|
Face Detection (F32)
|
100% |
1250
14.9 IPS |
|
|
Face Detection (F16)
|
100% |
1267
15.1 IPS |
|
|
Face Detection (I8)
|
86% |
2355
28.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
1287
9.98 IPS |
|
|
Depth Estimation (F16)
|
100% |
1301
10.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
2244
17.4 IPS |
|
|
Style Transfer (F32)
|
100% |
2415
3.18 IPS |
|
|
Style Transfer (F16)
|
100% |
2475
3.26 IPS |
|
|
Style Transfer (I8)
|
98% |
4832
6.36 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
861
30.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
861
30.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1818
64.9 IPS |
|
|
Text Classification (F32)
|
100% |
519
746.3 IPS |
|
|
Text Classification (F16)
|
100% |
530
761.2 IPS |
|
|
Text Classification (I8)
|
92% |
374
536.9 IPS |
|
|
Machine Translation (F32)
|
100% |
1480
27.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1424
26.2 IPS |
|
|
Machine Translation (I8)
|
64% |
525
9.65 IPS |
