samsung SM-A366W
Geekbench AI Score
925
Single Precision Score
1663
Half Precision Score
2106
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | March 25 2026 08:47 AM |
| 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% |
949
176.5 IPS |
|
|
Image Classification (Q)
|
99% |
1445
269.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
535
8.68 IPS |
|
|
Image Segmentation (HP)
|
100% |
1048
17.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
1682
27.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
1903
2.22 IPS |
|
|
Pose Estimation (HP)
|
92% |
4276
5.02 IPS |
|
|
Pose Estimation (Q)
|
96% |
3805
4.46 IPS |
|
|
Object Detection (SP)
|
100% |
455
36.1 IPS |
|
|
Object Detection (HP)
|
97% |
900
71.7 IPS |
|
|
Object Detection (Q)
|
85% |
1403
113.0 IPS |
|
|
Face Detection (SP)
|
100% |
1124
13.4 IPS |
|
|
Face Detection (HP)
|
100% |
2175
25.8 IPS |
|
|
Face Detection (Q)
|
97% |
3451
41.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
1615
12.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
3246
25.1 IPS |
|
|
Depth Estimation (Q)
|
64% |
3433
31.7 IPS |
|
|
Style Transfer (SP)
|
89% |
3709
4.81 IPS |
|
|
Style Transfer (HP)
|
88% |
4962
6.44 IPS |
|
|
Style Transfer (Q)
|
98% |
8282
10.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
873
32.2 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
1750
65.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2087
77.3 IPS |
|
|
Text Classification (SP)
|
100% |
495
660.6 IPS |
|
|
Text Classification (HP)
|
100% |
806
1.08 KIPS |
|
|
Text Classification (Q)
|
93% |
949
1.27 KIPS |
|
|
Machine Translation (SP)
|
100% |
745
12.8 IPS |
|
|
Machine Translation (HP)
|
96% |
860
14.9 IPS |
|
|
Machine Translation (Q)
|
55% |
681
18.3 IPS |
