samsung SM-A215U
Geekbench AI Score
275
Single Precision Score
271
Half Precision Score
307
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | February 02 2026 10:11 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM MT6765V/CA |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | samsung SM-A215U |
| Model ID | samsung SM-A215U |
| 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% |
145
26.9 IPS |
|
|
Image Classification (HP)
|
100% |
113
21.0 IPS |
|
|
Image Classification (Q)
|
100% |
185
34.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
185
3.00 IPS |
|
|
Image Segmentation (HP)
|
100% |
198
3.20 IPS |
|
|
Image Segmentation (Q)
|
98% |
335
5.45 IPS |
|
|
Pose Estimation (SP)
|
100% |
689
0.80 IPS |
|
|
Pose Estimation (HP)
|
100% |
617
0.72 IPS |
|
|
Pose Estimation (Q)
|
84% |
494
0.59 IPS |
|
|
Object Detection (SP)
|
100% |
145
11.5 IPS |
|
|
Object Detection (HP)
|
100% |
144
11.4 IPS |
|
|
Object Detection (Q)
|
83% |
200
16.2 IPS |
|
|
Face Detection (SP)
|
100% |
355
4.22 IPS |
|
|
Face Detection (HP)
|
100% |
359
4.26 IPS |
|
|
Face Detection (Q)
|
95% |
581
6.94 IPS |
|
|
Depth Estimation (SP)
|
100% |
495
3.82 IPS |
|
|
Depth Estimation (HP)
|
99% |
419
3.23 IPS |
|
|
Depth Estimation (Q)
|
64% |
432
3.96 IPS |
|
|
Style Transfer (SP)
|
89% |
1220
1.58 IPS |
|
|
Style Transfer (HP)
|
89% |
1231
1.60 IPS |
|
|
Style Transfer (Q)
|
98% |
1217
1.57 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
225
8.32 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
219
8.08 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
297
11.0 IPS |
|
|
Text Classification (SP)
|
100% |
122
163.0 IPS |
|
|
Text Classification (HP)
|
100% |
140
187.5 IPS |
|
|
Text Classification (Q)
|
88% |
149
200.5 IPS |
|
|
Machine Translation (SP)
|
100% |
162
2.79 IPS |
|
|
Machine Translation (HP)
|
100% |
193
3.33 IPS |
|
|
Machine Translation (Q)
|
50% |
92
3.26 IPS |
