samsung SM-X216B
Geekbench AI Score
190
Single Precision Score
290
Half Precision Score
303
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | Vaitek |
| Upload Date | November 15 2024 12:04 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-X216B |
| Model ID | samsung SM-X216B |
| Motherboard | holi |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 7.21 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
108
20.0 IPS |
|
|
Image Classification (HP)
|
100% |
177
33.0 IPS |
|
|
Image Classification (Q)
|
97% |
191
35.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
155
2.51 IPS |
|
|
Image Segmentation (HP)
|
100% |
284
4.61 IPS |
|
|
Image Segmentation (Q)
|
98% |
276
4.49 IPS |
|
|
Pose Estimation (SP)
|
100% |
215
0.25 IPS |
|
|
Pose Estimation (HP)
|
100% |
266
0.31 IPS |
|
|
Pose Estimation (Q)
|
95% |
263
0.31 IPS |
|
|
Object Detection (SP)
|
100% |
96
7.63 IPS |
|
|
Object Detection (HP)
|
100% |
147
11.7 IPS |
|
|
Object Detection (Q)
|
89% |
163
13.0 IPS |
|
|
Face Detection (SP)
|
100% |
264
3.14 IPS |
|
|
Face Detection (HP)
|
100% |
491
5.84 IPS |
|
|
Face Detection (Q)
|
97% |
504
6.01 IPS |
|
|
Depth Estimation (SP)
|
100% |
247
1.91 IPS |
|
|
Depth Estimation (HP)
|
99% |
420
3.25 IPS |
|
|
Depth Estimation (Q)
|
62% |
347
3.29 IPS |
|
|
Style Transfer (SP)
|
100% |
490
0.63 IPS |
|
|
Style Transfer (HP)
|
100% |
1049
1.35 IPS |
|
|
Style Transfer (Q)
|
98% |
1044
1.35 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
128
4.74 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
219
8.10 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
217
8.03 IPS |
|
|
Text Classification (SP)
|
100% |
163
217.0 IPS |
|
|
Text Classification (HP)
|
100% |
162
216.6 IPS |
|
|
Text Classification (Q)
|
91% |
311
418.4 IPS |
|
|
Machine Translation (SP)
|
100% |
279
4.80 IPS |
|
|
Machine Translation (HP)
|
100% |
280
4.83 IPS |
|
|
Machine Translation (Q)
|
57% |
242
5.92 IPS |
