samsung SM-A215W
Geekbench AI Score
250
Single Precision Score
256
Half Precision Score
272
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 28 2024 02:37 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% |
128
23.9 IPS |
|
|
Image Classification (HP)
|
100% |
140
26.0 IPS |
|
|
Image Classification (Q)
|
100% |
200
37.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
170
2.75 IPS |
|
|
Image Segmentation (HP)
|
100% |
178
2.89 IPS |
|
|
Image Segmentation (Q)
|
98% |
289
4.70 IPS |
|
|
Pose Estimation (SP)
|
100% |
633
0.74 IPS |
|
|
Pose Estimation (HP)
|
100% |
591
0.69 IPS |
|
|
Pose Estimation (Q)
|
84% |
417
0.50 IPS |
|
|
Object Detection (SP)
|
100% |
121
9.57 IPS |
|
|
Object Detection (HP)
|
100% |
128
10.1 IPS |
|
|
Object Detection (Q)
|
83% |
177
14.3 IPS |
|
|
Face Detection (SP)
|
100% |
324
3.85 IPS |
|
|
Face Detection (HP)
|
100% |
321
3.81 IPS |
|
|
Face Detection (Q)
|
95% |
458
5.47 IPS |
|
|
Depth Estimation (SP)
|
100% |
416
3.21 IPS |
|
|
Depth Estimation (HP)
|
99% |
431
3.32 IPS |
|
|
Depth Estimation (Q)
|
64% |
415
3.80 IPS |
|
|
Style Transfer (SP)
|
89% |
980
1.27 IPS |
|
|
Style Transfer (HP)
|
89% |
1000
1.30 IPS |
|
|
Style Transfer (Q)
|
98% |
962
1.24 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
208
7.70 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
204
7.52 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
237
8.79 IPS |
|
|
Text Classification (SP)
|
100% |
123
164.2 IPS |
|
|
Text Classification (HP)
|
100% |
125
166.5 IPS |
|
|
Text Classification (Q)
|
88% |
139
187.4 IPS |
|
|
Machine Translation (SP)
|
100% |
176
3.02 IPS |
|
|
Machine Translation (HP)
|
100% |
182
3.14 IPS |
|
|
Machine Translation (Q)
|
50% |
87
3.10 IPS |
