samsung SM-F741B
Geekbench ML Score
665
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 26 2024 01:12 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-F741B |
| Model ID | samsung SM-F741B |
| 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% |
313
58.6 IPS |
|
|
Image Classification (F16)
|
100% |
303
56.7 IPS |
|
|
Image Classification (I8)
|
97% |
800
149.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
380
6.34 IPS |
|
|
Image Segmentation (F16)
|
100% |
374
6.25 IPS |
|
|
Image Segmentation (I8)
|
98% |
752
12.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
526
0.64 IPS |
|
|
Pose Estimation (F16)
|
100% |
517
0.63 IPS |
|
|
Pose Estimation (I8)
|
100% |
2006
2.43 IPS |
|
|
Object Detection (F32)
|
100% |
309
23.0 IPS |
|
|
Object Detection (F16)
|
100% |
311
23.2 IPS |
|
|
Object Detection (I8)
|
61% |
837
62.5 IPS |
|
|
Face Detection (F32)
|
100% |
747
8.88 IPS |
|
|
Face Detection (F16)
|
100% |
733
8.72 IPS |
|
|
Face Detection (I8)
|
86% |
1738
20.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
649
5.03 IPS |
|
|
Depth Estimation (F16)
|
100% |
646
5.01 IPS |
|
|
Depth Estimation (I8)
|
95% |
1792
13.9 IPS |
|
|
Style Transfer (F32)
|
100% |
1002
1.32 IPS |
|
|
Style Transfer (F16)
|
100% |
992
1.31 IPS |
|
|
Style Transfer (I8)
|
98% |
2535
3.33 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
352
12.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
357
12.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1217
43.5 IPS |
|
|
Text Classification (F32)
|
100% |
426
612.4 IPS |
|
|
Text Classification (F16)
|
100% |
428
615.6 IPS |
|
|
Text Classification (I8)
|
92% |
710
1.02 KIPS |
|
|
Machine Translation (F32)
|
100% |
704
13.0 IPS |
|
|
Machine Translation (F16)
|
100% |
683
12.6 IPS |
|
|
Machine Translation (I8)
|
64% |
803
14.8 IPS |
