samsung SM-A366W
Geekbench AI Score
839
Single Precision Score
816
Half Precision Score
1489
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 07 2025 11:31 PM |
| Views | 8 |
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% |
449
83.5 IPS |
|
|
Image Classification (HP)
|
100% |
452
84.1 IPS |
|
|
Image Classification (Q)
|
100% |
1435
266.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
516
8.36 IPS |
|
|
Image Segmentation (HP)
|
100% |
490
7.94 IPS |
|
|
Image Segmentation (Q)
|
98% |
1661
27.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
2043
2.38 IPS |
|
|
Pose Estimation (HP)
|
100% |
1935
2.26 IPS |
|
|
Pose Estimation (Q)
|
84% |
3613
4.29 IPS |
|
|
Object Detection (SP)
|
100% |
440
34.9 IPS |
|
|
Object Detection (HP)
|
100% |
437
34.7 IPS |
|
|
Object Detection (Q)
|
83% |
1382
111.7 IPS |
|
|
Face Detection (SP)
|
100% |
1105
13.1 IPS |
|
|
Face Detection (HP)
|
100% |
1101
13.1 IPS |
|
|
Face Detection (Q)
|
95% |
3244
38.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
781
6.02 IPS |
|
|
Depth Estimation (HP)
|
99% |
786
6.05 IPS |
|
|
Depth Estimation (Q)
|
64% |
3416
31.3 IPS |
|
|
Style Transfer (SP)
|
89% |
3635
4.72 IPS |
|
|
Style Transfer (HP)
|
89% |
3596
4.67 IPS |
|
|
Style Transfer (Q)
|
98% |
7349
9.48 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
815
30.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
832
30.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1881
69.7 IPS |
|
|
Text Classification (SP)
|
100% |
456
608.6 IPS |
|
|
Text Classification (HP)
|
100% |
422
563.5 IPS |
|
|
Text Classification (Q)
|
88% |
799
1.08 KIPS |
|
|
Machine Translation (SP)
|
100% |
719
12.4 IPS |
|
|
Machine Translation (HP)
|
100% |
646
11.1 IPS |
|
|
Machine Translation (Q)
|
50% |
37
1.31 IPS |
