samsung SM-X216B
Geekbench AI Score
525
Single Precision Score
517
Half Precision Score
1026
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | Vaitek |
| Upload Date | November 15 2024 09:44 AM |
| Views | 18 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
239
44.5 IPS |
|
|
Image Classification (HP)
|
100% |
233
43.2 IPS |
|
|
Image Classification (Q)
|
100% |
722
134.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
297
4.82 IPS |
|
|
Image Segmentation (HP)
|
100% |
305
4.95 IPS |
|
|
Image Segmentation (Q)
|
98% |
830
13.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
1098
1.28 IPS |
|
|
Pose Estimation (HP)
|
100% |
1055
1.23 IPS |
|
|
Pose Estimation (Q)
|
84% |
1609
1.91 IPS |
|
|
Object Detection (SP)
|
100% |
229
18.2 IPS |
|
|
Object Detection (HP)
|
100% |
215
17.0 IPS |
|
|
Object Detection (Q)
|
83% |
703
56.8 IPS |
|
|
Face Detection (SP)
|
100% |
746
8.87 IPS |
|
|
Face Detection (HP)
|
100% |
765
9.09 IPS |
|
|
Face Detection (Q)
|
95% |
1611
19.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
936
7.21 IPS |
|
|
Depth Estimation (HP)
|
99% |
929
7.16 IPS |
|
|
Depth Estimation (Q)
|
64% |
1592
14.6 IPS |
|
|
Style Transfer (SP)
|
89% |
1791
2.32 IPS |
|
|
Style Transfer (HP)
|
89% |
1838
2.39 IPS |
|
|
Style Transfer (Q)
|
98% |
3730
4.81 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
521
19.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
514
19.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
941
34.9 IPS |
|
|
Text Classification (SP)
|
100% |
292
390.3 IPS |
|
|
Text Classification (HP)
|
100% |
290
387.0 IPS |
|
|
Text Classification (Q)
|
88% |
587
791.2 IPS |
|
|
Machine Translation (SP)
|
100% |
474
8.16 IPS |
|
|
Machine Translation (HP)
|
100% |
442
7.61 IPS |
|
|
Machine Translation (Q)
|
50% |
364
12.9 IPS |
