samsung SM-F956B
Geekbench ML Score
867
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 15 2024 04:40 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-F956B |
| Model ID | samsung SM-F956B |
| 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% |
572
107.1 IPS |
|
|
Image Classification (F16)
|
100% |
571
106.8 IPS |
|
|
Image Classification (I8)
|
97% |
871
163.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
621
10.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
585
9.77 IPS |
|
|
Image Segmentation (I8)
|
98% |
712
11.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1225
1.48 IPS |
|
|
Pose Estimation (F16)
|
100% |
1172
1.42 IPS |
|
|
Pose Estimation (I8)
|
100% |
5102
6.18 IPS |
|
|
Object Detection (F32)
|
100% |
406
30.3 IPS |
|
|
Object Detection (F16)
|
100% |
427
31.9 IPS |
|
|
Object Detection (I8)
|
61% |
783
58.5 IPS |
|
|
Face Detection (F32)
|
100% |
1046
12.4 IPS |
|
|
Face Detection (F16)
|
100% |
1046
12.4 IPS |
|
|
Face Detection (I8)
|
86% |
1369
16.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
547
4.24 IPS |
|
|
Depth Estimation (F16)
|
100% |
1031
7.99 IPS |
|
|
Depth Estimation (I8)
|
95% |
1690
13.1 IPS |
|
|
Style Transfer (F32)
|
100% |
1869
2.46 IPS |
|
|
Style Transfer (F16)
|
100% |
1803
2.37 IPS |
|
|
Style Transfer (I8)
|
98% |
3875
5.10 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
565
20.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
527
18.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1416
50.6 IPS |
|
|
Text Classification (F32)
|
100% |
393
565.4 IPS |
|
|
Text Classification (F16)
|
100% |
424
609.2 IPS |
|
|
Text Classification (I8)
|
92% |
315
452.9 IPS |
|
|
Machine Translation (F32)
|
100% |
1064
19.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1082
19.9 IPS |
|
|
Machine Translation (I8)
|
64% |
402
7.39 IPS |
