samsung SM-M156B
Geekbench AI Score
269
Single Precision Score
482
Half Precision Score
401
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | Beamish |
| Upload Date | November 17 2025 03:11 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
147
27.4 IPS |
|
|
Image Classification (HP)
|
100% |
288
53.6 IPS |
|
|
Image Classification (Q)
|
97% |
263
49.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
223
3.61 IPS |
|
|
Image Segmentation (HP)
|
100% |
513
8.32 IPS |
|
|
Image Segmentation (Q)
|
98% |
478
7.77 IPS |
|
|
Pose Estimation (SP)
|
100% |
959
1.12 IPS |
|
|
Pose Estimation (HP)
|
100% |
1869
2.18 IPS |
|
|
Pose Estimation (Q)
|
95% |
1843
2.16 IPS |
|
|
Object Detection (SP)
|
100% |
131
10.4 IPS |
|
|
Object Detection (HP)
|
99% |
279
22.2 IPS |
|
|
Object Detection (Q)
|
83% |
266
21.5 IPS |
|
|
Face Detection (SP)
|
100% |
545
6.47 IPS |
|
|
Face Detection (HP)
|
100% |
1210
14.4 IPS |
|
|
Face Detection (Q)
|
96% |
1062
12.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
664
5.11 IPS |
|
|
Depth Estimation (HP)
|
98% |
1336
10.3 IPS |
|
|
Depth Estimation (Q)
|
62% |
1055
10.0 IPS |
|
|
Style Transfer (SP)
|
100% |
1805
2.32 IPS |
|
|
Style Transfer (HP)
|
100% |
3813
4.90 IPS |
|
|
Style Transfer (Q)
|
98% |
3720
4.80 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
361
13.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
708
26.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
677
25.1 IPS |
|
|
Text Classification (SP)
|
35% |
9
83.0 IPS |
|
|
Text Classification (HP)
|
29% |
7
119.0 IPS |
|
|
Text Classification (Q)
|
31% |
9
124.7 IPS |
|
|
Machine Translation (SP)
|
100% |
230
3.95 IPS |
|
|
Machine Translation (HP)
|
100% |
290
5.00 IPS |
|
|
Machine Translation (Q)
|
43% |
70
4.08 IPS |
