Samsung Galaxy S20+
Geekbench ML Score
440
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 01 2025 01:04 PM |
| Views | 8 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Samsung Galaxy S20+ |
| Model ID | samsung SM-G985F |
| Motherboard | exynos990 |
| Governor | energy_step |
| CPU Information | |
|---|---|
| Name | ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 83 architecture 8 variant 1 part 4 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.50 GHz |
| Cluster 3 | 2 Cores @ 2.73 GHz |
| Memory Information | |
|---|---|
| Size | 7.27 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
184
34.5 IPS |
|
|
Image Classification (F16)
|
100% |
179
33.6 IPS |
|
|
Image Classification (I8)
|
97% |
433
81.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
334
5.57 IPS |
|
|
Image Segmentation (F16)
|
100% |
406
6.78 IPS |
|
|
Image Segmentation (I8)
|
98% |
466
7.78 IPS |
|
|
Pose Estimation (F32)
|
100% |
1397
1.69 IPS |
|
|
Pose Estimation (F16)
|
100% |
4927
5.97 IPS |
|
|
Pose Estimation (I8)
|
100% |
1324
1.60 IPS |
|
|
Object Detection (F32)
|
100% |
191
14.3 IPS |
|
|
Object Detection (F16)
|
100% |
190
14.2 IPS |
|
|
Object Detection (I8)
|
61% |
489
36.5 IPS |
|
|
Face Detection (F32)
|
100% |
459
5.45 IPS |
|
|
Face Detection (F16)
|
100% |
455
5.41 IPS |
|
|
Face Detection (I8)
|
86% |
880
10.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
396
3.07 IPS |
|
|
Depth Estimation (F16)
|
100% |
394
3.06 IPS |
|
|
Depth Estimation (I8)
|
95% |
1099
8.53 IPS |
|
|
Style Transfer (F32)
|
100% |
854
1.12 IPS |
|
|
Style Transfer (F16)
|
100% |
851
1.12 IPS |
|
|
Style Transfer (I8)
|
98% |
746
0.98 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
573
20.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
804
28.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
816
29.1 IPS |
|
|
Text Classification (F32)
|
100% |
64
92.6 IPS |
|
|
Text Classification (F16)
|
100% |
66
94.2 IPS |
|
|
Text Classification (I8)
|
92% |
59
84.6 IPS |
|
|
Machine Translation (F32)
|
100% |
419
7.71 IPS |
|
|
Machine Translation (F16)
|
100% |
418
7.70 IPS |
|
|
Machine Translation (I8)
|
64% |
515
9.48 IPS |
