samsung SM-A366W
Geekbench AI Score
537
Single Precision Score
947
Half Precision Score
752
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | February 14 2026 09:26 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
403
75.0 IPS |
|
|
Image Classification (HP)
|
100% |
698
129.9 IPS |
|
|
Image Classification (Q)
|
100% |
657
122.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
578
9.36 IPS |
|
|
Image Segmentation (HP)
|
100% |
1041
16.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
969
15.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
1994
2.33 IPS |
|
|
Pose Estimation (HP)
|
99% |
3829
4.48 IPS |
|
|
Pose Estimation (Q)
|
96% |
3782
4.43 IPS |
|
|
Object Detection (SP)
|
100% |
350
27.7 IPS |
|
|
Object Detection (HP)
|
99% |
608
48.2 IPS |
|
|
Object Detection (Q)
|
87% |
577
46.4 IPS |
|
|
Face Detection (SP)
|
100% |
1039
12.3 IPS |
|
|
Face Detection (HP)
|
100% |
2042
24.3 IPS |
|
|
Face Detection (Q)
|
97% |
1782
21.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
1182
9.10 IPS |
|
|
Depth Estimation (HP)
|
98% |
2316
17.9 IPS |
|
|
Depth Estimation (Q)
|
61% |
1722
17.0 IPS |
|
|
Style Transfer (SP)
|
100% |
2163
2.78 IPS |
|
|
Style Transfer (HP)
|
100% |
4491
5.77 IPS |
|
|
Style Transfer (Q)
|
98% |
4465
5.76 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
539
19.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1056
39.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1023
37.9 IPS |
|
|
Text Classification (SP)
|
35% |
22
218.3 IPS |
|
|
Text Classification (HP)
|
35% |
35
318.7 IPS |
|
|
Text Classification (Q)
|
33% |
26
312.8 IPS |
|
|
Machine Translation (SP)
|
100% |
392
6.76 IPS |
|
|
Machine Translation (HP)
|
97% |
439
7.60 IPS |
|
|
Machine Translation (Q)
|
43% |
115
6.56 IPS |
