samsung SM-A366W
Geekbench AI Score
934
Single Precision Score
1681
Half Precision Score
2113
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | April 14 2026 10:04 AM |
| Views | 3 |
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
85.0 IPS |
|
|
Image Classification (HP)
|
100% |
947
176.2 IPS |
|
|
Image Classification (Q)
|
99% |
1440
268.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
536
8.69 IPS |
|
|
Image Segmentation (HP)
|
100% |
1058
17.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
1684
27.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
2049
2.39 IPS |
|
|
Pose Estimation (HP)
|
92% |
4338
5.10 IPS |
|
|
Pose Estimation (Q)
|
96% |
3822
4.48 IPS |
|
|
Object Detection (SP)
|
100% |
456
36.2 IPS |
|
|
Object Detection (HP)
|
97% |
907
72.2 IPS |
|
|
Object Detection (Q)
|
85% |
1401
112.9 IPS |
|
|
Face Detection (SP)
|
100% |
1162
13.8 IPS |
|
|
Face Detection (HP)
|
100% |
2187
26.0 IPS |
|
|
Face Detection (Q)
|
97% |
3442
41.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
1623
12.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
3221
24.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
3440
31.7 IPS |
|
|
Style Transfer (SP)
|
89% |
3727
4.84 IPS |
|
|
Style Transfer (HP)
|
88% |
4905
6.37 IPS |
|
|
Style Transfer (Q)
|
98% |
8549
11.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
873
32.2 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
1741
64.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2088
77.4 IPS |
|
|
Text Classification (SP)
|
100% |
484
646.0 IPS |
|
|
Text Classification (HP)
|
100% |
810
1.08 KIPS |
|
|
Text Classification (Q)
|
93% |
950
1.28 KIPS |
|
|
Machine Translation (SP)
|
100% |
744
12.8 IPS |
|
|
Machine Translation (HP)
|
96% |
941
16.3 IPS |
|
|
Machine Translation (Q)
|
55% |
681
18.3 IPS |
