samsung SCG25
Geekbench ML Score
496
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 18 2024 11:05 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SCG25 |
| Model ID | samsung SCG25 |
| 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 | 6.93 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
288
53.9 IPS |
|
|
Image Classification (F16)
|
100% |
282
52.7 IPS |
|
|
Image Classification (I8)
|
97% |
736
137.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
338
5.64 IPS |
|
|
Image Segmentation (F16)
|
100% |
336
5.61 IPS |
|
|
Image Segmentation (I8)
|
98% |
715
11.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
457
0.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
457
0.55 IPS |
|
|
Pose Estimation (I8)
|
100% |
1867
2.26 IPS |
|
|
Object Detection (F32)
|
100% |
284
21.2 IPS |
|
|
Object Detection (F16)
|
100% |
284
21.2 IPS |
|
|
Object Detection (I8)
|
61% |
698
52.1 IPS |
|
|
Face Detection (F32)
|
100% |
634
7.53 IPS |
|
|
Face Detection (F16)
|
100% |
600
7.13 IPS |
|
|
Face Detection (I8)
|
86% |
1228
14.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
471
3.65 IPS |
|
|
Depth Estimation (F16)
|
100% |
428
3.32 IPS |
|
|
Depth Estimation (I8)
|
95% |
1074
8.33 IPS |
|
|
Style Transfer (F32)
|
100% |
629
0.83 IPS |
|
|
Style Transfer (F16)
|
100% |
549
0.72 IPS |
|
|
Style Transfer (I8)
|
98% |
1389
1.83 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
197
7.02 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
225
8.02 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
734
26.2 IPS |
|
|
Text Classification (F32)
|
100% |
243
348.6 IPS |
|
|
Text Classification (F16)
|
100% |
243
348.9 IPS |
|
|
Text Classification (I8)
|
92% |
425
611.4 IPS |
|
|
Machine Translation (F32)
|
100% |
522
9.60 IPS |
|
|
Machine Translation (F16)
|
100% |
546
10.0 IPS |
|
|
Machine Translation (I8)
|
64% |
617
11.4 IPS |
