samsung SM-A366W
Geekbench AI Score
931
Single Precision Score
1670
Half Precision Score
2101
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | February 14 2026 09:21 AM |
| Views | 6 |
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% |
451
83.9 IPS |
|
|
Image Classification (HP)
|
100% |
940
174.8 IPS |
|
|
Image Classification (Q)
|
99% |
1442
269.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
533
8.64 IPS |
|
|
Image Segmentation (HP)
|
100% |
1057
17.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
1686
27.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
2007
2.34 IPS |
|
|
Pose Estimation (HP)
|
92% |
4280
5.03 IPS |
|
|
Pose Estimation (Q)
|
96% |
3822
4.48 IPS |
|
|
Object Detection (SP)
|
100% |
458
36.3 IPS |
|
|
Object Detection (HP)
|
97% |
913
72.7 IPS |
|
|
Object Detection (Q)
|
85% |
1395
112.4 IPS |
|
|
Face Detection (SP)
|
100% |
1167
13.9 IPS |
|
|
Face Detection (HP)
|
100% |
2169
25.8 IPS |
|
|
Face Detection (Q)
|
97% |
3442
41.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
1601
12.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
3248
25.1 IPS |
|
|
Depth Estimation (Q)
|
64% |
3420
31.6 IPS |
|
|
Style Transfer (SP)
|
89% |
3726
4.84 IPS |
|
|
Style Transfer (HP)
|
88% |
4648
6.04 IPS |
|
|
Style Transfer (Q)
|
98% |
8613
11.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
873
32.2 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
1769
65.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2083
77.2 IPS |
|
|
Text Classification (SP)
|
100% |
498
664.7 IPS |
|
|
Text Classification (HP)
|
100% |
814
1.09 KIPS |
|
|
Text Classification (Q)
|
93% |
955
1.28 KIPS |
|
|
Machine Translation (SP)
|
100% |
738
12.7 IPS |
|
|
Machine Translation (HP)
|
96% |
925
16.0 IPS |
|
|
Machine Translation (Q)
|
55% |
643
17.3 IPS |
