samsung SM-F956B
Geekbench ML Score
689
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 18 2024 12:22 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
324
60.6 IPS |
|
|
Image Classification (F16)
|
100% |
317
59.3 IPS |
|
|
Image Classification (I8)
|
97% |
822
153.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
390
6.51 IPS |
|
|
Image Segmentation (F16)
|
100% |
387
6.46 IPS |
|
|
Image Segmentation (I8)
|
98% |
787
13.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
533
0.65 IPS |
|
|
Pose Estimation (F16)
|
100% |
525
0.64 IPS |
|
|
Pose Estimation (I8)
|
100% |
2090
2.53 IPS |
|
|
Object Detection (F32)
|
100% |
324
24.2 IPS |
|
|
Object Detection (F16)
|
100% |
325
24.2 IPS |
|
|
Object Detection (I8)
|
61% |
884
66.0 IPS |
|
|
Face Detection (F32)
|
100% |
757
9.01 IPS |
|
|
Face Detection (F16)
|
100% |
745
8.86 IPS |
|
|
Face Detection (I8)
|
86% |
1798
21.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
664
5.15 IPS |
|
|
Depth Estimation (F16)
|
100% |
661
5.12 IPS |
|
|
Depth Estimation (I8)
|
95% |
1875
14.5 IPS |
|
|
Style Transfer (F32)
|
100% |
1048
1.38 IPS |
|
|
Style Transfer (F16)
|
100% |
1037
1.36 IPS |
|
|
Style Transfer (I8)
|
98% |
2584
3.40 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
377
13.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
377
13.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1268
45.3 IPS |
|
|
Text Classification (F32)
|
100% |
444
638.5 IPS |
|
|
Text Classification (F16)
|
100% |
447
642.4 IPS |
|
|
Text Classification (I8)
|
92% |
713
1.03 KIPS |
|
|
Machine Translation (F32)
|
100% |
738
13.6 IPS |
|
|
Machine Translation (F16)
|
100% |
716
13.2 IPS |
|
|
Machine Translation (I8)
|
64% |
828
15.2 IPS |
