Samsung Galaxy S21+ 5G
Geekbench ML Score
664
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | Cho_Seung_Woo |
| Upload Date | February 23 2024 02:58 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S21+ 5G |
| Model ID | samsung SM-G996N |
| Motherboard | exynos2100 |
| Governor | energy_step |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3396 revision 0 |
| Base Frequency | 2.21 GHz |
| Cluster 1 | 4 Cores @ 2.21 GHz |
| Cluster 2 | 3 Cores @ 2.81 GHz |
| Cluster 3 | 1 Core @ 2.91 GHz |
| Memory Information | |
|---|---|
| Size | 7.03 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
438
82.0 IPS |
|
|
Image Classification (F16)
|
100% |
760
142.3 IPS |
|
|
Image Classification (I8)
|
97% |
713
133.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
575
9.60 IPS |
|
|
Image Segmentation (F16)
|
100% |
958
16.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
935
15.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
266
0.32 IPS |
|
|
Pose Estimation (F16)
|
100% |
340
0.41 IPS |
|
|
Pose Estimation (I8)
|
100% |
338
0.41 IPS |
|
|
Object Detection (F32)
|
100% |
355
26.5 IPS |
|
|
Object Detection (F16)
|
100% |
558
41.6 IPS |
|
|
Object Detection (I8)
|
62% |
555
41.4 IPS |
|
|
Face Detection (F32)
|
100% |
1498
17.8 IPS |
|
|
Face Detection (F16)
|
98% |
2273
27.0 IPS |
|
|
Face Detection (I8)
|
86% |
2098
24.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
579
4.49 IPS |
|
|
Depth Estimation (F16)
|
100% |
763
5.91 IPS |
|
|
Depth Estimation (I8)
|
95% |
756
5.86 IPS |
|
|
Style Transfer (F32)
|
100% |
1209
1.59 IPS |
|
|
Style Transfer (F16)
|
100% |
2096
2.76 IPS |
|
|
Style Transfer (I8)
|
98% |
2089
2.75 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
400
14.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
678
24.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
674
24.1 IPS |
|
|
Text Classification (F32)
|
100% |
285
409.8 IPS |
|
|
Text Classification (F16)
|
100% |
287
412.8 IPS |
|
|
Text Classification (I8)
|
92% |
512
735.7 IPS |
|
|
Machine Translation (F32)
|
100% |
473
8.71 IPS |
|
|
Machine Translation (F16)
|
100% |
464
8.54 IPS |
|
|
Machine Translation (I8)
|
64% |
539
9.92 IPS |
