samsung SM-F956B
Geekbench ML Score
819
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 15 2024 12:31 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% |
126
23.6 IPS |
|
|
Image Classification (F16)
|
100% |
137
25.6 IPS |
|
|
Image Classification (I8)
|
97% |
160
30.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
362
6.04 IPS |
|
|
Image Segmentation (F16)
|
100% |
423
7.07 IPS |
|
|
Image Segmentation (I8)
|
98% |
566
9.45 IPS |
|
|
Pose Estimation (F32)
|
100% |
1069
1.29 IPS |
|
|
Pose Estimation (F16)
|
100% |
1104
1.34 IPS |
|
|
Pose Estimation (I8)
|
100% |
4256
5.15 IPS |
|
|
Object Detection (F32)
|
100% |
449
33.5 IPS |
|
|
Object Detection (F16)
|
100% |
468
34.9 IPS |
|
|
Object Detection (I8)
|
61% |
861
64.3 IPS |
|
|
Face Detection (F32)
|
100% |
1158
13.8 IPS |
|
|
Face Detection (F16)
|
100% |
1209
14.4 IPS |
|
|
Face Detection (I8)
|
86% |
2201
26.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
1179
9.14 IPS |
|
|
Depth Estimation (F16)
|
100% |
1210
9.38 IPS |
|
|
Depth Estimation (I8)
|
95% |
2114
16.4 IPS |
|
|
Style Transfer (F32)
|
100% |
2320
3.05 IPS |
|
|
Style Transfer (F16)
|
100% |
2048
2.69 IPS |
|
|
Style Transfer (I8)
|
98% |
4385
5.77 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
646
23.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
691
24.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1658
59.2 IPS |
|
|
Text Classification (F32)
|
100% |
493
707.8 IPS |
|
|
Text Classification (F16)
|
100% |
468
672.9 IPS |
|
|
Text Classification (I8)
|
92% |
373
536.6 IPS |
|
|
Machine Translation (F32)
|
100% |
1327
24.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1390
25.6 IPS |
|
|
Machine Translation (I8)
|
64% |
513
9.43 IPS |
