samsung SM-F946B
Geekbench ML Score
621
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 20 2024 08:43 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-F946B |
| Model ID | samsung SM-F946B |
| Motherboard | kalama |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.36 GHz |
| Memory Information | |
|---|---|
| Size | 10.87 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
293
54.7 IPS |
|
|
Image Classification (F16)
|
100% |
282
52.7 IPS |
|
|
Image Classification (I8)
|
97% |
715
133.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
339
5.66 IPS |
|
|
Image Segmentation (F16)
|
100% |
337
5.63 IPS |
|
|
Image Segmentation (I8)
|
98% |
707
11.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
469
0.57 IPS |
|
|
Pose Estimation (F16)
|
100% |
465
0.56 IPS |
|
|
Pose Estimation (I8)
|
100% |
1974
2.39 IPS |
|
|
Object Detection (F32)
|
100% |
295
22.0 IPS |
|
|
Object Detection (F16)
|
100% |
297
22.2 IPS |
|
|
Object Detection (I8)
|
61% |
832
62.1 IPS |
|
|
Face Detection (F32)
|
100% |
676
8.04 IPS |
|
|
Face Detection (F16)
|
100% |
666
7.92 IPS |
|
|
Face Detection (I8)
|
86% |
1493
17.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
586
4.54 IPS |
|
|
Depth Estimation (F16)
|
100% |
583
4.52 IPS |
|
|
Depth Estimation (I8)
|
95% |
1689
13.1 IPS |
|
|
Style Transfer (F32)
|
100% |
956
1.26 IPS |
|
|
Style Transfer (F16)
|
100% |
953
1.25 IPS |
|
|
Style Transfer (I8)
|
98% |
2428
3.19 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
339
12.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
336
12.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1177
42.0 IPS |
|
|
Text Classification (F32)
|
100% |
416
598.0 IPS |
|
|
Text Classification (F16)
|
100% |
431
619.2 IPS |
|
|
Text Classification (I8)
|
92% |
679
976.2 IPS |
|
|
Machine Translation (F32)
|
100% |
658
12.1 IPS |
|
|
Machine Translation (F16)
|
100% |
649
11.9 IPS |
|
|
Machine Translation (I8)
|
64% |
705
13.0 IPS |
