samsung SM-F741B
Geekbench ML Score
391
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 18 2024 08:10 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% |
309
57.8 IPS |
|
|
Image Classification (F16)
|
100% |
298
55.8 IPS |
|
|
Image Classification (I8)
|
97% |
783
146.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
367
6.13 IPS |
|
|
Image Segmentation (F16)
|
100% |
329
5.49 IPS |
|
|
Image Segmentation (I8)
|
98% |
562
9.39 IPS |
|
|
Pose Estimation (F32)
|
100% |
398
0.48 IPS |
|
|
Pose Estimation (F16)
|
100% |
370
0.45 IPS |
|
|
Pose Estimation (I8)
|
100% |
1067
1.29 IPS |
|
|
Object Detection (F32)
|
100% |
166
12.4 IPS |
|
|
Object Detection (F16)
|
100% |
164
12.3 IPS |
|
|
Object Detection (I8)
|
61% |
419
31.3 IPS |
|
|
Face Detection (F32)
|
100% |
390
4.64 IPS |
|
|
Face Detection (F16)
|
100% |
388
4.61 IPS |
|
|
Face Detection (I8)
|
86% |
848
10.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
340
2.64 IPS |
|
|
Depth Estimation (F16)
|
100% |
341
2.65 IPS |
|
|
Depth Estimation (I8)
|
95% |
878
6.81 IPS |
|
|
Style Transfer (F32)
|
100% |
551
0.72 IPS |
|
|
Style Transfer (F16)
|
100% |
552
0.73 IPS |
|
|
Style Transfer (I8)
|
98% |
1311
1.72 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
183
6.53 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
182
6.51 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
599
21.4 IPS |
|
|
Text Classification (F32)
|
100% |
200
287.6 IPS |
|
|
Text Classification (F16)
|
100% |
200
288.1 IPS |
|
|
Text Classification (I8)
|
92% |
325
466.9 IPS |
|
|
Machine Translation (F32)
|
100% |
362
6.67 IPS |
|
|
Machine Translation (F16)
|
100% |
366
6.74 IPS |
|
|
Machine Translation (I8)
|
64% |
395
7.26 IPS |
