samsung SM-A366W
Geekbench AI Score
769
Single Precision Score
798
Half Precision Score
1429
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 21 2025 10:05 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-A366W |
| Model ID | samsung SM-A366W |
| Motherboard | parrot |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 2 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 5.16 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
195
36.3 IPS |
|
|
Image Classification (HP)
|
100% |
460
85.6 IPS |
|
|
Image Classification (Q)
|
100% |
1450
269.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
509
8.24 IPS |
|
|
Image Segmentation (HP)
|
100% |
527
8.54 IPS |
|
|
Image Segmentation (Q)
|
98% |
1658
27.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
2009
2.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
1847
2.16 IPS |
|
|
Pose Estimation (Q)
|
84% |
3309
3.92 IPS |
|
|
Object Detection (SP)
|
100% |
434
34.4 IPS |
|
|
Object Detection (HP)
|
100% |
454
36.0 IPS |
|
|
Object Detection (Q)
|
83% |
1379
111.4 IPS |
|
|
Face Detection (SP)
|
100% |
1107
13.2 IPS |
|
|
Face Detection (HP)
|
100% |
628
7.46 IPS |
|
|
Face Detection (Q)
|
95% |
2956
35.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
747
5.76 IPS |
|
|
Depth Estimation (HP)
|
99% |
832
6.41 IPS |
|
|
Depth Estimation (Q)
|
64% |
3418
31.3 IPS |
|
|
Style Transfer (SP)
|
89% |
3636
4.72 IPS |
|
|
Style Transfer (HP)
|
89% |
3615
4.69 IPS |
|
|
Style Transfer (Q)
|
98% |
7380
9.52 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
805
29.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
838
31.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1957
72.5 IPS |
|
|
Text Classification (SP)
|
100% |
485
646.9 IPS |
|
|
Text Classification (HP)
|
100% |
462
617.0 IPS |
|
|
Text Classification (Q)
|
88% |
856
1.15 KIPS |
|
|
Machine Translation (SP)
|
100% |
720
12.4 IPS |
|
|
Machine Translation (HP)
|
100% |
707
12.2 IPS |
|
|
Machine Translation (Q)
|
50% |
26
0.91 IPS |
