samsung SM-A366W
Geekbench AI Score
936
Single Precision Score
1667
Half Precision Score
2105
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | March 21 2026 12:34 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% |
461
85.7 IPS |
|
|
Image Classification (HP)
|
100% |
941
175.0 IPS |
|
|
Image Classification (Q)
|
99% |
1446
269.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
537
8.71 IPS |
|
|
Image Segmentation (HP)
|
100% |
1039
16.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
1674
27.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2017
2.35 IPS |
|
|
Pose Estimation (HP)
|
92% |
4286
5.03 IPS |
|
|
Pose Estimation (Q)
|
96% |
3822
4.48 IPS |
|
|
Object Detection (SP)
|
100% |
461
36.6 IPS |
|
|
Object Detection (HP)
|
97% |
889
70.7 IPS |
|
|
Object Detection (Q)
|
85% |
1356
109.3 IPS |
|
|
Face Detection (SP)
|
100% |
1155
13.7 IPS |
|
|
Face Detection (HP)
|
100% |
2214
26.3 IPS |
|
|
Face Detection (Q)
|
97% |
3437
41.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
1615
12.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
3260
25.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
3429
31.6 IPS |
|
|
Style Transfer (SP)
|
89% |
3765
4.89 IPS |
|
|
Style Transfer (HP)
|
88% |
4667
6.06 IPS |
|
|
Style Transfer (Q)
|
98% |
8581
11.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
868
32.0 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
1739
64.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2089
77.4 IPS |
|
|
Text Classification (SP)
|
100% |
498
665.2 IPS |
|
|
Text Classification (HP)
|
100% |
810
1.08 KIPS |
|
|
Text Classification (Q)
|
93% |
945
1.27 KIPS |
|
|
Machine Translation (SP)
|
100% |
746
12.9 IPS |
|
|
Machine Translation (HP)
|
96% |
943
16.3 IPS |
|
|
Machine Translation (Q)
|
55% |
683
18.3 IPS |
