samsung SM-A215W
Geekbench AI Score
250
Single Precision Score
249
Half Precision Score
269
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 28 2024 02:56 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM MT6765V/CA |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | samsung SM-A215W |
| Model ID | samsung SM-A215W |
| Motherboard | a21 |
| CPU Information | |
|---|---|
| Name | ARM MT6765V/CA |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3331 revision 4 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.30 GHz |
| Memory Information | |
|---|---|
| Size | 2.69 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
151
28.2 IPS |
|
|
Image Classification (HP)
|
100% |
139
25.8 IPS |
|
|
Image Classification (Q)
|
100% |
226
42.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
182
2.96 IPS |
|
|
Image Segmentation (HP)
|
100% |
183
2.96 IPS |
|
|
Image Segmentation (Q)
|
98% |
322
5.23 IPS |
|
|
Pose Estimation (SP)
|
100% |
566
0.66 IPS |
|
|
Pose Estimation (HP)
|
100% |
549
0.64 IPS |
|
|
Pose Estimation (Q)
|
84% |
405
0.48 IPS |
|
|
Object Detection (SP)
|
100% |
117
9.27 IPS |
|
|
Object Detection (HP)
|
100% |
118
9.36 IPS |
|
|
Object Detection (Q)
|
83% |
164
13.3 IPS |
|
|
Face Detection (SP)
|
100% |
305
3.62 IPS |
|
|
Face Detection (HP)
|
100% |
312
3.71 IPS |
|
|
Face Detection (Q)
|
95% |
464
5.54 IPS |
|
|
Depth Estimation (SP)
|
100% |
396
3.05 IPS |
|
|
Depth Estimation (HP)
|
99% |
420
3.23 IPS |
|
|
Depth Estimation (Q)
|
64% |
367
3.36 IPS |
|
|
Style Transfer (SP)
|
89% |
1002
1.30 IPS |
|
|
Style Transfer (HP)
|
89% |
1016
1.32 IPS |
|
|
Style Transfer (Q)
|
98% |
1002
1.29 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
202
7.47 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
203
7.50 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
228
8.45 IPS |
|
|
Text Classification (SP)
|
100% |
136
182.0 IPS |
|
|
Text Classification (HP)
|
100% |
130
173.9 IPS |
|
|
Text Classification (Q)
|
88% |
134
180.3 IPS |
|
|
Machine Translation (SP)
|
100% |
161
2.78 IPS |
|
|
Machine Translation (HP)
|
100% |
161
2.77 IPS |
|
|
Machine Translation (Q)
|
50% |
79
2.81 IPS |
