samsung SM-X216B
Geekbench AI Score
544
Single Precision Score
543
Half Precision Score
1055
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | Benchmarker |
| Upload Date | October 30 2025 08:42 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
240
44.7 IPS |
|
|
Image Classification (HP)
|
100% |
240
44.6 IPS |
|
|
Image Classification (Q)
|
100% |
717
133.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
313
5.07 IPS |
|
|
Image Segmentation (HP)
|
100% |
313
5.08 IPS |
|
|
Image Segmentation (Q)
|
98% |
828
13.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
1169
1.36 IPS |
|
|
Pose Estimation (HP)
|
100% |
1149
1.34 IPS |
|
|
Pose Estimation (Q)
|
84% |
1688
2.00 IPS |
|
|
Object Detection (SP)
|
100% |
233
18.5 IPS |
|
|
Object Detection (HP)
|
100% |
233
18.5 IPS |
|
|
Object Detection (Q)
|
83% |
710
57.4 IPS |
|
|
Face Detection (SP)
|
100% |
769
9.14 IPS |
|
|
Face Detection (HP)
|
100% |
770
9.15 IPS |
|
|
Face Detection (Q)
|
95% |
1709
20.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
1010
7.78 IPS |
|
|
Depth Estimation (HP)
|
99% |
1011
7.79 IPS |
|
|
Depth Estimation (Q)
|
64% |
1615
14.8 IPS |
|
|
Style Transfer (SP)
|
89% |
1950
2.53 IPS |
|
|
Style Transfer (HP)
|
89% |
1981
2.57 IPS |
|
|
Style Transfer (Q)
|
98% |
4025
5.19 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
529
19.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
535
19.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1005
37.2 IPS |
|
|
Text Classification (SP)
|
100% |
291
388.0 IPS |
|
|
Text Classification (HP)
|
100% |
288
383.9 IPS |
|
|
Text Classification (Q)
|
88% |
576
776.8 IPS |
|
|
Machine Translation (SP)
|
100% |
476
8.20 IPS |
|
|
Machine Translation (HP)
|
100% |
472
8.13 IPS |
|
|
Machine Translation (Q)
|
50% |
374
13.3 IPS |
