samsung SM-A366W
Geekbench AI Score
534
Single Precision Score
942
Half Precision Score
744
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | February 15 2026 10:38 AM |
| Views | 9 |
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% |
407
75.7 IPS |
|
|
Image Classification (HP)
|
100% |
712
132.3 IPS |
|
|
Image Classification (Q)
|
100% |
659
122.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
593
9.61 IPS |
|
|
Image Segmentation (HP)
|
100% |
1011
16.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
962
15.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
1985
2.32 IPS |
|
|
Pose Estimation (HP)
|
99% |
3820
4.47 IPS |
|
|
Pose Estimation (Q)
|
96% |
3788
4.44 IPS |
|
|
Object Detection (SP)
|
100% |
348
27.6 IPS |
|
|
Object Detection (HP)
|
99% |
598
47.5 IPS |
|
|
Object Detection (Q)
|
87% |
560
45.0 IPS |
|
|
Face Detection (SP)
|
100% |
1043
12.4 IPS |
|
|
Face Detection (HP)
|
100% |
2084
24.8 IPS |
|
|
Face Detection (Q)
|
97% |
1818
21.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
1171
9.02 IPS |
|
|
Depth Estimation (HP)
|
98% |
2292
17.7 IPS |
|
|
Depth Estimation (Q)
|
61% |
1729
17.0 IPS |
|
|
Style Transfer (SP)
|
100% |
2097
2.70 IPS |
|
|
Style Transfer (HP)
|
100% |
4294
5.52 IPS |
|
|
Style Transfer (Q)
|
98% |
4299
5.54 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
533
19.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1023
37.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
985
36.5 IPS |
|
|
Text Classification (SP)
|
35% |
22
215.2 IPS |
|
|
Text Classification (HP)
|
35% |
35
314.8 IPS |
|
|
Text Classification (Q)
|
33% |
26
311.4 IPS |
|
|
Machine Translation (SP)
|
100% |
382
6.58 IPS |
|
|
Machine Translation (HP)
|
97% |
456
7.88 IPS |
|
|
Machine Translation (Q)
|
43% |
112
6.36 IPS |
