samsung SM-S9210
Geekbench ML Score
619
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 15 2024 03:36 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S9210 |
| Model ID | samsung SM-S9210 |
| 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% |
282
52.8 IPS |
|
|
Image Classification (F16)
|
100% |
277
51.8 IPS |
|
|
Image Classification (I8)
|
97% |
728
136.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
331
5.53 IPS |
|
|
Image Segmentation (F16)
|
100% |
337
5.63 IPS |
|
|
Image Segmentation (I8)
|
98% |
717
12.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
454
0.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
450
0.55 IPS |
|
|
Pose Estimation (I8)
|
100% |
1867
2.26 IPS |
|
|
Object Detection (F32)
|
100% |
293
21.9 IPS |
|
|
Object Detection (F16)
|
100% |
290
21.7 IPS |
|
|
Object Detection (I8)
|
61% |
814
60.8 IPS |
|
|
Face Detection (F32)
|
100% |
672
7.99 IPS |
|
|
Face Detection (F16)
|
100% |
664
7.89 IPS |
|
|
Face Detection (I8)
|
86% |
1632
19.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
582
4.51 IPS |
|
|
Depth Estimation (F16)
|
100% |
579
4.49 IPS |
|
|
Depth Estimation (I8)
|
95% |
1697
13.2 IPS |
|
|
Style Transfer (F32)
|
100% |
941
1.24 IPS |
|
|
Style Transfer (F16)
|
100% |
938
1.23 IPS |
|
|
Style Transfer (I8)
|
98% |
2349
3.09 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
331
11.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
339
12.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1185
42.3 IPS |
|
|
Text Classification (F32)
|
100% |
417
599.4 IPS |
|
|
Text Classification (F16)
|
100% |
417
599.5 IPS |
|
|
Text Classification (I8)
|
92% |
688
989.0 IPS |
|
|
Machine Translation (F32)
|
100% |
669
12.3 IPS |
|
|
Machine Translation (F16)
|
100% |
657
12.1 IPS |
|
|
Machine Translation (I8)
|
64% |
782
14.4 IPS |
