samsung SM-A716V
Geekbench ML Score
375
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | December 21 2024 11:32 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | samsung SM-A716V |
| Model ID | samsung SM-A716V |
| Motherboard | lito |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 15 part 2052 revision 14 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 1 Core @ 2.21 GHz |
| Cluster 3 | 1 Core @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.24 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
210
39.2 IPS |
|
|
Image Classification (F16)
|
100% |
203
38.0 IPS |
|
|
Image Classification (I8)
|
97% |
449
84.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
295
4.93 IPS |
|
|
Image Segmentation (F16)
|
100% |
297
4.96 IPS |
|
|
Image Segmentation (I8)
|
98% |
371
6.19 IPS |
|
|
Pose Estimation (F32)
|
100% |
429
0.52 IPS |
|
|
Pose Estimation (F16)
|
100% |
421
0.51 IPS |
|
|
Pose Estimation (I8)
|
100% |
1970
2.39 IPS |
|
|
Object Detection (F32)
|
100% |
225
16.8 IPS |
|
|
Object Detection (F16)
|
100% |
227
17.0 IPS |
|
|
Object Detection (I8)
|
61% |
396
29.6 IPS |
|
|
Face Detection (F32)
|
100% |
328
3.90 IPS |
|
|
Face Detection (F16)
|
100% |
333
3.96 IPS |
|
|
Face Detection (I8)
|
86% |
621
7.39 IPS |
|
|
Depth Estimation (F32)
|
100% |
335
2.60 IPS |
|
|
Depth Estimation (F16)
|
100% |
341
2.64 IPS |
|
|
Depth Estimation (I8)
|
95% |
658
5.10 IPS |
|
|
Style Transfer (F32)
|
100% |
544
0.72 IPS |
|
|
Style Transfer (F16)
|
100% |
542
0.71 IPS |
|
|
Style Transfer (I8)
|
98% |
1830
2.41 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
231
8.26 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
233
8.33 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
861
30.8 IPS |
|
|
Text Classification (F32)
|
100% |
256
368.1 IPS |
|
|
Text Classification (F16)
|
100% |
229
329.8 IPS |
|
|
Text Classification (I8)
|
92% |
192
275.3 IPS |
|
|
Machine Translation (F32)
|
100% |
488
8.97 IPS |
|
|
Machine Translation (F16)
|
100% |
233
4.28 IPS |
|
|
Machine Translation (I8)
|
64% |
237
4.37 IPS |
