samsung SM-F956U1
Geekbench ML Score
1138
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 11 2024 09:11 PM |
| 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% |
644
120.5 IPS |
|
|
Image Classification (F16)
|
100% |
625
117.0 IPS |
|
|
Image Classification (I8)
|
97% |
1037
194.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
800
13.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
802
13.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
923
15.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
1353
1.64 IPS |
|
|
Pose Estimation (F16)
|
100% |
1344
1.63 IPS |
|
|
Pose Estimation (I8)
|
100% |
5798
7.02 IPS |
|
|
Object Detection (F32)
|
100% |
601
44.9 IPS |
|
|
Object Detection (F16)
|
100% |
542
40.5 IPS |
|
|
Object Detection (I8)
|
61% |
1260
94.1 IPS |
|
|
Face Detection (F32)
|
100% |
1240
14.7 IPS |
|
|
Face Detection (F16)
|
100% |
1235
14.7 IPS |
|
|
Face Detection (I8)
|
86% |
2219
26.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1232
9.56 IPS |
|
|
Depth Estimation (F16)
|
100% |
1237
9.59 IPS |
|
|
Depth Estimation (I8)
|
95% |
2234
17.3 IPS |
|
|
Style Transfer (F32)
|
100% |
2394
3.15 IPS |
|
|
Style Transfer (F16)
|
100% |
2375
3.12 IPS |
|
|
Style Transfer (I8)
|
98% |
4588
6.04 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
860
30.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
771
27.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1858
66.3 IPS |
|
|
Text Classification (F32)
|
100% |
513
737.8 IPS |
|
|
Text Classification (F16)
|
100% |
529
759.9 IPS |
|
|
Text Classification (I8)
|
92% |
413
593.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1446
26.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1352
24.9 IPS |
|
|
Machine Translation (I8)
|
64% |
556
10.2 IPS |
