samsung SM-A366B
Geekbench AI Score
827
Single Precision Score
827
Half Precision Score
1409
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | ululalbab |
| Upload Date | June 25 2025 03:13 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-A366B |
| Model ID | samsung SM-A366B |
| 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 | 11.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
454
84.5 IPS |
|
|
Image Classification (HP)
|
100% |
453
84.2 IPS |
|
|
Image Classification (Q)
|
100% |
1437
267.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
498
8.07 IPS |
|
|
Image Segmentation (HP)
|
100% |
527
8.54 IPS |
|
|
Image Segmentation (Q)
|
98% |
1665
27.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1906
2.22 IPS |
|
|
Pose Estimation (HP)
|
100% |
1849
2.16 IPS |
|
|
Pose Estimation (Q)
|
84% |
3219
3.82 IPS |
|
|
Object Detection (SP)
|
100% |
426
33.8 IPS |
|
|
Object Detection (HP)
|
100% |
414
32.8 IPS |
|
|
Object Detection (Q)
|
83% |
1174
94.8 IPS |
|
|
Face Detection (SP)
|
100% |
1077
12.8 IPS |
|
|
Face Detection (HP)
|
100% |
1120
13.3 IPS |
|
|
Face Detection (Q)
|
95% |
3272
39.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
757
5.83 IPS |
|
|
Depth Estimation (HP)
|
99% |
784
6.04 IPS |
|
|
Depth Estimation (Q)
|
64% |
3409
31.2 IPS |
|
|
Style Transfer (SP)
|
89% |
3714
4.82 IPS |
|
|
Style Transfer (HP)
|
89% |
3560
4.62 IPS |
|
|
Style Transfer (Q)
|
98% |
7378
9.51 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
836
30.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
836
30.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1884
69.8 IPS |
|
|
Text Classification (SP)
|
100% |
456
609.1 IPS |
|
|
Text Classification (HP)
|
100% |
453
604.3 IPS |
|
|
Text Classification (Q)
|
88% |
852
1.15 KIPS |
|
|
Machine Translation (SP)
|
100% |
711
12.2 IPS |
|
|
Machine Translation (HP)
|
100% |
696
12.0 IPS |
|
|
Machine Translation (Q)
|
50% |
26
0.91 IPS |
