samsung SM-F956B
Geekbench ML Score
651
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 15 2024 12:38 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% |
310
58.1 IPS |
|
|
Image Classification (F16)
|
100% |
297
55.5 IPS |
|
|
Image Classification (I8)
|
97% |
785
146.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
373
6.23 IPS |
|
|
Image Segmentation (F16)
|
100% |
365
6.10 IPS |
|
|
Image Segmentation (I8)
|
98% |
743
12.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
489
0.59 IPS |
|
|
Pose Estimation (F16)
|
100% |
479
0.58 IPS |
|
|
Pose Estimation (I8)
|
100% |
1989
2.41 IPS |
|
|
Object Detection (F32)
|
100% |
303
22.6 IPS |
|
|
Object Detection (F16)
|
100% |
309
23.0 IPS |
|
|
Object Detection (I8)
|
61% |
834
62.3 IPS |
|
|
Face Detection (F32)
|
100% |
740
8.80 IPS |
|
|
Face Detection (F16)
|
100% |
724
8.61 IPS |
|
|
Face Detection (I8)
|
86% |
1664
19.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
631
4.89 IPS |
|
|
Depth Estimation (F16)
|
100% |
623
4.83 IPS |
|
|
Depth Estimation (I8)
|
95% |
1769
13.7 IPS |
|
|
Style Transfer (F32)
|
100% |
968
1.27 IPS |
|
|
Style Transfer (F16)
|
100% |
971
1.28 IPS |
|
|
Style Transfer (I8)
|
98% |
2471
3.25 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
348
12.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
351
12.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1199
42.8 IPS |
|
|
Text Classification (F32)
|
100% |
419
601.8 IPS |
|
|
Text Classification (F16)
|
100% |
424
609.3 IPS |
|
|
Text Classification (I8)
|
92% |
700
1.01 KIPS |
|
|
Machine Translation (F32)
|
100% |
703
12.9 IPS |
|
|
Machine Translation (F16)
|
100% |
678
12.5 IPS |
|
|
Machine Translation (I8)
|
64% |
794
14.6 IPS |
