samsung SM-A217N
Geekbench AI Score
295
Single Precision Score
317
Half Precision Score
310
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 22 2024 05:55 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | samsung SM-A217N |
| Model ID | samsung SM-A217N |
| Motherboard | exynos850 |
| Governor | energy_step |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3333 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 8 Cores @ 2.00 GHz |
| Memory Information | |
|---|---|
| Size | 2.64 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
146
27.1 IPS |
|
|
Image Classification (HP)
|
100% |
163
30.3 IPS |
|
|
Image Classification (Q)
|
100% |
236
43.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
110
1.78 IPS |
|
|
Image Segmentation (HP)
|
100% |
215
3.48 IPS |
|
|
Image Segmentation (Q)
|
98% |
334
5.43 IPS |
|
|
Pose Estimation (SP)
|
100% |
829
0.97 IPS |
|
|
Pose Estimation (HP)
|
100% |
827
0.97 IPS |
|
|
Pose Estimation (Q)
|
84% |
545
0.65 IPS |
|
|
Object Detection (SP)
|
100% |
177
14.0 IPS |
|
|
Object Detection (HP)
|
100% |
159
12.6 IPS |
|
|
Object Detection (Q)
|
83% |
187
15.1 IPS |
|
|
Face Detection (SP)
|
100% |
384
4.57 IPS |
|
|
Face Detection (HP)
|
100% |
387
4.59 IPS |
|
|
Face Detection (Q)
|
95% |
485
5.79 IPS |
|
|
Depth Estimation (SP)
|
100% |
495
3.82 IPS |
|
|
Depth Estimation (HP)
|
99% |
509
3.92 IPS |
|
|
Depth Estimation (Q)
|
64% |
468
4.28 IPS |
|
|
Style Transfer (SP)
|
89% |
1375
1.78 IPS |
|
|
Style Transfer (HP)
|
89% |
1390
1.81 IPS |
|
|
Style Transfer (Q)
|
98% |
1292
1.67 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
270
9.97 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
278
10.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
272
10.1 IPS |
|
|
Text Classification (SP)
|
100% |
138
183.9 IPS |
|
|
Text Classification (HP)
|
100% |
133
177.7 IPS |
|
|
Text Classification (Q)
|
88% |
148
199.3 IPS |
|
|
Machine Translation (SP)
|
100% |
222
3.82 IPS |
|
|
Machine Translation (HP)
|
100% |
221
3.80 IPS |
|
|
Machine Translation (Q)
|
50% |
88
3.11 IPS |
