samsung SM-A366W
Geekbench AI Score
887
Single Precision Score
869
Half Precision Score
1798
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | October 14 2025 02:07 AM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| 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 | 5.25 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
459
85.3 IPS |
|
|
Image Classification (HP)
|
100% |
454
84.4 IPS |
|
|
Image Classification (Q)
|
100% |
1332
247.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
513
8.32 IPS |
|
|
Image Segmentation (HP)
|
100% |
509
8.24 IPS |
|
|
Image Segmentation (Q)
|
98% |
1545
25.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2005
2.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
1888
2.20 IPS |
|
|
Pose Estimation (Q)
|
84% |
3770
4.47 IPS |
|
|
Object Detection (SP)
|
100% |
452
35.9 IPS |
|
|
Object Detection (HP)
|
100% |
444
35.2 IPS |
|
|
Object Detection (Q)
|
83% |
1174
94.8 IPS |
|
|
Face Detection (SP)
|
100% |
1068
12.7 IPS |
|
|
Face Detection (HP)
|
100% |
1080
12.8 IPS |
|
|
Face Detection (Q)
|
95% |
3016
36.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
1521
11.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
1524
11.7 IPS |
|
|
Depth Estimation (Q)
|
64% |
2967
27.2 IPS |
|
|
Style Transfer (SP)
|
89% |
3349
4.35 IPS |
|
|
Style Transfer (HP)
|
89% |
3359
4.36 IPS |
|
|
Style Transfer (Q)
|
98% |
7337
9.46 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
836
30.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
843
31.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1874
69.5 IPS |
|
|
Text Classification (SP)
|
100% |
423
564.3 IPS |
|
|
Text Classification (HP)
|
100% |
419
558.8 IPS |
|
|
Text Classification (Q)
|
88% |
796
1.07 KIPS |
|
|
Machine Translation (SP)
|
100% |
735
12.7 IPS |
|
|
Machine Translation (HP)
|
100% |
651
11.2 IPS |
|
|
Machine Translation (Q)
|
50% |
398
14.1 IPS |
