samsung SM-M346B
Geekbench ML Score
299
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 17 2024 06:33 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-M346B |
| Model ID | samsung SM-M346B |
| Motherboard | s5e8825 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 5.26 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
166
31.1 IPS |
|
|
Image Classification (F16)
|
100% |
297
55.7 IPS |
|
|
Image Classification (I8)
|
97% |
284
53.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
226
3.78 IPS |
|
|
Image Segmentation (F16)
|
100% |
375
6.26 IPS |
|
|
Image Segmentation (I8)
|
98% |
370
6.18 IPS |
|
|
Pose Estimation (F32)
|
100% |
148
0.18 IPS |
|
|
Pose Estimation (F16)
|
100% |
174
0.21 IPS |
|
|
Pose Estimation (I8)
|
100% |
173
0.21 IPS |
|
|
Object Detection (F32)
|
100% |
138
10.3 IPS |
|
|
Object Detection (F16)
|
100% |
222
16.6 IPS |
|
|
Object Detection (I8)
|
62% |
218
16.3 IPS |
|
|
Face Detection (F32)
|
100% |
550
6.54 IPS |
|
|
Face Detection (F16)
|
98% |
839
9.97 IPS |
|
|
Face Detection (I8)
|
86% |
772
9.18 IPS |
|
|
Depth Estimation (F32)
|
100% |
296
2.29 IPS |
|
|
Depth Estimation (F16)
|
100% |
379
2.94 IPS |
|
|
Depth Estimation (I8)
|
95% |
376
2.92 IPS |
|
|
Style Transfer (F32)
|
100% |
583
0.77 IPS |
|
|
Style Transfer (F16)
|
100% |
823
1.08 IPS |
|
|
Style Transfer (I8)
|
98% |
823
1.08 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
165
5.89 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
255
9.11 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
254
9.06 IPS |
|
|
Text Classification (F32)
|
100% |
155
223.4 IPS |
|
|
Text Classification (F16)
|
100% |
155
222.2 IPS |
|
|
Text Classification (I8)
|
92% |
312
448.6 IPS |
|
|
Machine Translation (F32)
|
100% |
287
5.28 IPS |
|
|
Machine Translation (F16)
|
100% |
288
5.29 IPS |
|
|
Machine Translation (I8)
|
64% |
385
7.09 IPS |
