samsung SM-A366W
Geekbench AI Score
905
Single Precision Score
1598
Half Precision Score
1972
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | February 15 2026 10:33 AM |
| Views | 10 |
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% |
454
84.5 IPS |
|
|
Image Classification (HP)
|
100% |
947
176.0 IPS |
|
|
Image Classification (Q)
|
99% |
1435
267.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
532
8.63 IPS |
|
|
Image Segmentation (HP)
|
100% |
1025
16.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
1666
27.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1997
2.33 IPS |
|
|
Pose Estimation (HP)
|
92% |
4083
4.80 IPS |
|
|
Pose Estimation (Q)
|
96% |
3799
4.45 IPS |
|
|
Object Detection (SP)
|
100% |
457
36.2 IPS |
|
|
Object Detection (HP)
|
97% |
881
70.1 IPS |
|
|
Object Detection (Q)
|
85% |
1344
108.3 IPS |
|
|
Face Detection (SP)
|
100% |
1127
13.4 IPS |
|
|
Face Detection (HP)
|
100% |
2140
25.4 IPS |
|
|
Face Detection (Q)
|
97% |
3197
38.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
1543
11.9 IPS |
|
|
Depth Estimation (HP)
|
98% |
3076
23.8 IPS |
|
|
Depth Estimation (Q)
|
64% |
3159
29.2 IPS |
|
|
Style Transfer (SP)
|
89% |
3603
4.68 IPS |
|
|
Style Transfer (HP)
|
88% |
4427
5.75 IPS |
|
|
Style Transfer (Q)
|
98% |
7503
9.68 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
803
29.6 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
1714
63.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1914
70.9 IPS |
|
|
Text Classification (SP)
|
100% |
460
613.7 IPS |
|
|
Text Classification (HP)
|
100% |
747
996.8 IPS |
|
|
Text Classification (Q)
|
93% |
876
1.18 KIPS |
|
|
Machine Translation (SP)
|
100% |
726
12.5 IPS |
|
|
Machine Translation (HP)
|
96% |
838
14.5 IPS |
|
|
Machine Translation (Q)
|
55% |
575
15.4 IPS |
