Samsung Galaxy A51 5G
Geekbench ML Score
239
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 04 2024 12:12 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Samsung Galaxy A51 5G |
| Model ID | samsung SM-A516N |
| Motherboard | exynos980 |
| Governor | energy_step |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3341 revision 0 |
| Base Frequency | 1.79 GHz |
| Cluster 1 | 6 Cores @ 1.79 GHz |
| Cluster 2 | 2 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 5.20 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
160
30.0 IPS |
|
|
Image Classification (F16)
|
100% |
224
41.9 IPS |
|
|
Image Classification (I8)
|
97% |
215
40.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
201
3.35 IPS |
|
|
Image Segmentation (F16)
|
100% |
279
4.67 IPS |
|
|
Image Segmentation (I8)
|
98% |
272
4.54 IPS |
|
|
Pose Estimation (F32)
|
100% |
99
0.12 IPS |
|
|
Pose Estimation (F16)
|
100% |
133
0.16 IPS |
|
|
Pose Estimation (I8)
|
100% |
133
0.16 IPS |
|
|
Object Detection (F32)
|
100% |
118
8.83 IPS |
|
|
Object Detection (F16)
|
100% |
161
12.1 IPS |
|
|
Object Detection (I8)
|
62% |
168
12.5 IPS |
|
|
Face Detection (F32)
|
100% |
475
5.65 IPS |
|
|
Face Detection (F16)
|
98% |
655
7.79 IPS |
|
|
Face Detection (I8)
|
86% |
599
7.12 IPS |
|
|
Depth Estimation (F32)
|
100% |
239
1.85 IPS |
|
|
Depth Estimation (F16)
|
100% |
290
2.25 IPS |
|
|
Depth Estimation (I8)
|
95% |
288
2.23 IPS |
|
|
Style Transfer (F32)
|
100% |
451
0.59 IPS |
|
|
Style Transfer (F16)
|
100% |
643
0.85 IPS |
|
|
Style Transfer (I8)
|
98% |
643
0.85 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
132
4.70 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
174
6.20 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
173
6.17 IPS |
|
|
Text Classification (F32)
|
100% |
145
208.3 IPS |
|
|
Text Classification (F16)
|
100% |
147
211.3 IPS |
|
|
Text Classification (I8)
|
92% |
277
398.3 IPS |
|
|
Machine Translation (F32)
|
100% |
260
4.78 IPS |
|
|
Machine Translation (F16)
|
100% |
261
4.79 IPS |
|
|
Machine Translation (I8)
|
64% |
330
6.08 IPS |
