samsung SM-A366W
Geekbench AI Score
840
Single Precision Score
815
Half Precision Score
1481
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 20 2025 01:55 AM |
| Views | 3 |
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% |
446
83.0 IPS |
|
|
Image Classification (HP)
|
100% |
450
83.7 IPS |
|
|
Image Classification (Q)
|
100% |
1445
268.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
530
8.60 IPS |
|
|
Image Segmentation (HP)
|
100% |
528
8.56 IPS |
|
|
Image Segmentation (Q)
|
98% |
1630
26.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
2001
2.33 IPS |
|
|
Pose Estimation (HP)
|
100% |
1882
2.20 IPS |
|
|
Pose Estimation (Q)
|
84% |
3768
4.47 IPS |
|
|
Object Detection (SP)
|
100% |
451
35.7 IPS |
|
|
Object Detection (HP)
|
100% |
452
35.8 IPS |
|
|
Object Detection (Q)
|
83% |
1348
108.9 IPS |
|
|
Face Detection (SP)
|
100% |
1088
12.9 IPS |
|
|
Face Detection (HP)
|
100% |
1084
12.9 IPS |
|
|
Face Detection (Q)
|
95% |
3368
40.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
769
5.92 IPS |
|
|
Depth Estimation (HP)
|
99% |
762
5.87 IPS |
|
|
Depth Estimation (Q)
|
64% |
3418
31.3 IPS |
|
|
Style Transfer (SP)
|
89% |
3653
4.74 IPS |
|
|
Style Transfer (HP)
|
89% |
3312
4.30 IPS |
|
|
Style Transfer (Q)
|
98% |
7640
9.85 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
797
29.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
791
29.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1877
69.6 IPS |
|
|
Text Classification (SP)
|
100% |
465
620.9 IPS |
|
|
Text Classification (HP)
|
100% |
457
609.9 IPS |
|
|
Text Classification (Q)
|
88% |
857
1.16 KIPS |
|
|
Machine Translation (SP)
|
100% |
729
12.6 IPS |
|
|
Machine Translation (HP)
|
100% |
647
11.1 IPS |
|
|
Machine Translation (Q)
|
50% |
30
1.05 IPS |
