samsung SM-X216B
Geekbench AI Score
369
Single Precision Score
597
Half Precision Score
553
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | Benchmarker |
| Upload Date | October 30 2025 08:51 AM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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% |
257
47.9 IPS |
|
|
Image Classification (HP)
|
100% |
414
76.9 IPS |
|
|
Image Classification (Q)
|
99% |
391
72.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
377
6.12 IPS |
|
|
Image Segmentation (HP)
|
100% |
594
9.64 IPS |
|
|
Image Segmentation (Q)
|
98% |
561
9.13 IPS |
|
|
Pose Estimation (SP)
|
100% |
1425
1.66 IPS |
|
|
Pose Estimation (HP)
|
99% |
2284
2.66 IPS |
|
|
Pose Estimation (Q)
|
97% |
2258
2.64 IPS |
|
|
Object Detection (SP)
|
100% |
229
18.2 IPS |
|
|
Object Detection (HP)
|
99% |
349
27.7 IPS |
|
|
Object Detection (Q)
|
85% |
345
27.8 IPS |
|
|
Face Detection (SP)
|
100% |
782
9.29 IPS |
|
|
Face Detection (HP)
|
100% |
1346
16.0 IPS |
|
|
Face Detection (Q)
|
97% |
1179
14.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
872
6.72 IPS |
|
|
Depth Estimation (HP)
|
98% |
1456
11.3 IPS |
|
|
Depth Estimation (Q)
|
65% |
1211
10.9 IPS |
|
|
Style Transfer (SP)
|
100% |
1870
2.40 IPS |
|
|
Style Transfer (HP)
|
100% |
3607
4.64 IPS |
|
|
Style Transfer (Q)
|
98% |
3449
4.45 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
359
13.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
560
20.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
543
20.1 IPS |
|
|
Text Classification (SP)
|
35% |
14
139.7 IPS |
|
|
Text Classification (HP)
|
35% |
24
216.8 IPS |
|
|
Text Classification (Q)
|
35% |
24
214.9 IPS |
|
|
Machine Translation (SP)
|
100% |
232
4.00 IPS |
|
|
Machine Translation (HP)
|
97% |
314
5.44 IPS |
|
|
Machine Translation (Q)
|
64% |
247
5.08 IPS |
