samsung SM-M156B
Geekbench AI Score
477
Single Precision Score
488
Half Precision Score
915
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | Beamish |
| Upload Date | November 17 2025 03:00 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-M156B |
| Model ID | samsung SM-M156B |
| Motherboard | m15x |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.20 GHz |
| Memory Information | |
|---|---|
| Size | 3.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
203
37.7 IPS |
|
|
Image Classification (HP)
|
100% |
209
38.8 IPS |
|
|
Image Classification (Q)
|
100% |
626
116.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
265
4.29 IPS |
|
|
Image Segmentation (HP)
|
100% |
268
4.35 IPS |
|
|
Image Segmentation (Q)
|
98% |
702
11.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
1031
1.20 IPS |
|
|
Pose Estimation (HP)
|
100% |
1023
1.19 IPS |
|
|
Pose Estimation (Q)
|
84% |
1571
1.86 IPS |
|
|
Object Detection (SP)
|
100% |
212
16.8 IPS |
|
|
Object Detection (HP)
|
100% |
214
17.0 IPS |
|
|
Object Detection (Q)
|
83% |
609
49.2 IPS |
|
|
Face Detection (SP)
|
100% |
715
8.50 IPS |
|
|
Face Detection (HP)
|
100% |
712
8.46 IPS |
|
|
Face Detection (Q)
|
95% |
1425
17.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
787
6.06 IPS |
|
|
Depth Estimation (HP)
|
99% |
913
7.03 IPS |
|
|
Depth Estimation (Q)
|
64% |
1459
13.4 IPS |
|
|
Style Transfer (SP)
|
89% |
1743
2.26 IPS |
|
|
Style Transfer (HP)
|
89% |
1768
2.30 IPS |
|
|
Style Transfer (Q)
|
98% |
3619
4.67 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
459
17.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
462
17.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
874
32.4 IPS |
|
|
Text Classification (SP)
|
100% |
255
339.9 IPS |
|
|
Text Classification (HP)
|
100% |
260
347.2 IPS |
|
|
Text Classification (Q)
|
88% |
464
626.1 IPS |
|
|
Machine Translation (SP)
|
100% |
455
7.84 IPS |
|
|
Machine Translation (HP)
|
100% |
453
7.80 IPS |
|
|
Machine Translation (Q)
|
50% |
322
11.4 IPS |
