samsung SM-A366W
Geekbench AI Score
930
Single Precision Score
1672
Half Precision Score
2088
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | March 31 2026 08:38 PM |
| Views | 7 |
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% |
457
84.9 IPS |
|
|
Image Classification (HP)
|
100% |
947
176.1 IPS |
|
|
Image Classification (Q)
|
99% |
1443
269.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
540
8.76 IPS |
|
|
Image Segmentation (HP)
|
100% |
1042
16.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
1673
27.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2035
2.37 IPS |
|
|
Pose Estimation (HP)
|
92% |
4368
5.13 IPS |
|
|
Pose Estimation (Q)
|
96% |
3813
4.47 IPS |
|
|
Object Detection (SP)
|
100% |
460
36.5 IPS |
|
|
Object Detection (HP)
|
97% |
915
72.8 IPS |
|
|
Object Detection (Q)
|
85% |
1359
109.4 IPS |
|
|
Face Detection (SP)
|
100% |
1147
13.6 IPS |
|
|
Face Detection (HP)
|
100% |
2196
26.1 IPS |
|
|
Face Detection (Q)
|
97% |
3459
41.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
1613
12.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
3265
25.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
3305
30.5 IPS |
|
|
Style Transfer (SP)
|
89% |
3701
4.80 IPS |
|
|
Style Transfer (HP)
|
88% |
4944
6.42 IPS |
|
|
Style Transfer (Q)
|
98% |
8552
11.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
839
31.0 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
1735
64.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2079
77.0 IPS |
|
|
Text Classification (SP)
|
100% |
499
665.9 IPS |
|
|
Text Classification (HP)
|
100% |
811
1.08 KIPS |
|
|
Text Classification (Q)
|
93% |
952
1.28 KIPS |
|
|
Machine Translation (SP)
|
100% |
736
12.7 IPS |
|
|
Machine Translation (HP)
|
96% |
873
15.1 IPS |
|
|
Machine Translation (Q)
|
55% |
653
17.5 IPS |
