samsung SM-F946N
Geekbench ML Score
559
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 29 2024 05:04 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-F946N |
| Model ID | samsung SM-F946N |
| 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
54.9 IPS |
|
|
Image Classification (F16)
|
100% |
288
53.8 IPS |
|
|
Image Classification (I8)
|
97% |
709
132.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
344
5.75 IPS |
|
|
Image Segmentation (F16)
|
100% |
342
5.71 IPS |
|
|
Image Segmentation (I8)
|
98% |
706
11.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
472
0.57 IPS |
|
|
Pose Estimation (F16)
|
100% |
469
0.57 IPS |
|
|
Pose Estimation (I8)
|
100% |
1918
2.32 IPS |
|
|
Object Detection (F32)
|
100% |
287
21.5 IPS |
|
|
Object Detection (F16)
|
100% |
302
22.5 IPS |
|
|
Object Detection (I8)
|
61% |
820
61.2 IPS |
|
|
Face Detection (F32)
|
100% |
695
8.27 IPS |
|
|
Face Detection (F16)
|
100% |
674
8.01 IPS |
|
|
Face Detection (I8)
|
86% |
1512
18.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
591
4.58 IPS |
|
|
Depth Estimation (F16)
|
100% |
585
4.54 IPS |
|
|
Depth Estimation (I8)
|
95% |
1575
12.2 IPS |
|
|
Style Transfer (F32)
|
100% |
923
1.21 IPS |
|
|
Style Transfer (F16)
|
100% |
812
1.07 IPS |
|
|
Style Transfer (I8)
|
98% |
1966
2.59 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
261
9.33 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
259
9.24 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
892
31.9 IPS |
|
|
Text Classification (F32)
|
100% |
294
423.0 IPS |
|
|
Text Classification (F16)
|
100% |
294
422.2 IPS |
|
|
Text Classification (I8)
|
92% |
425
610.7 IPS |
|
|
Machine Translation (F32)
|
100% |
548
10.1 IPS |
|
|
Machine Translation (F16)
|
100% |
542
9.98 IPS |
|
|
Machine Translation (I8)
|
64% |
489
9.00 IPS |
