samsung SM-A366W
Geekbench AI Score
781
Single Precision Score
842
Half Precision Score
1460
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | August 28 2025 06:34 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% |
193
35.9 IPS |
|
|
Image Classification (HP)
|
100% |
447
83.1 IPS |
|
|
Image Classification (Q)
|
100% |
1434
266.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
532
8.62 IPS |
|
|
Image Segmentation (HP)
|
100% |
530
8.60 IPS |
|
|
Image Segmentation (Q)
|
98% |
1652
26.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
2033
2.37 IPS |
|
|
Pose Estimation (HP)
|
100% |
1992
2.32 IPS |
|
|
Pose Estimation (Q)
|
84% |
3618
4.29 IPS |
|
|
Object Detection (SP)
|
100% |
450
35.7 IPS |
|
|
Object Detection (HP)
|
100% |
452
35.8 IPS |
|
|
Object Detection (Q)
|
83% |
1261
101.9 IPS |
|
|
Face Detection (SP)
|
100% |
1111
13.2 IPS |
|
|
Face Detection (HP)
|
100% |
1116
13.3 IPS |
|
|
Face Detection (Q)
|
95% |
3371
40.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
784
6.04 IPS |
|
|
Depth Estimation (HP)
|
99% |
773
5.95 IPS |
|
|
Depth Estimation (Q)
|
64% |
3411
31.2 IPS |
|
|
Style Transfer (SP)
|
89% |
3667
4.76 IPS |
|
|
Style Transfer (HP)
|
89% |
3564
4.63 IPS |
|
|
Style Transfer (Q)
|
98% |
7342
9.47 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
853
31.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
857
31.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1904
70.6 IPS |
|
|
Text Classification (SP)
|
100% |
461
615.3 IPS |
|
|
Text Classification (HP)
|
100% |
456
608.6 IPS |
|
|
Text Classification (Q)
|
88% |
846
1.14 KIPS |
|
|
Machine Translation (SP)
|
100% |
724
12.5 IPS |
|
|
Machine Translation (HP)
|
100% |
707
12.2 IPS |
|
|
Machine Translation (Q)
|
50% |
30
1.06 IPS |
