samsung SM-A366W
Geekbench AI Score
847
Single Precision Score
830
Half Precision Score
1356
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | September 11 2025 02:29 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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 | 5.16 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
442
82.2 IPS |
|
|
Image Classification (HP)
|
100% |
443
82.4 IPS |
|
|
Image Classification (Q)
|
100% |
1445
268.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
515
8.35 IPS |
|
|
Image Segmentation (HP)
|
100% |
515
8.35 IPS |
|
|
Image Segmentation (Q)
|
98% |
1654
26.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
2008
2.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
1902
2.22 IPS |
|
|
Pose Estimation (Q)
|
84% |
3758
4.46 IPS |
|
|
Object Detection (SP)
|
100% |
452
35.8 IPS |
|
|
Object Detection (HP)
|
100% |
439
34.8 IPS |
|
|
Object Detection (Q)
|
83% |
1383
111.7 IPS |
|
|
Face Detection (SP)
|
100% |
1110
13.2 IPS |
|
|
Face Detection (HP)
|
100% |
1090
13.0 IPS |
|
|
Face Detection (Q)
|
95% |
3272
39.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
789
6.08 IPS |
|
|
Depth Estimation (HP)
|
99% |
818
6.30 IPS |
|
|
Depth Estimation (Q)
|
64% |
3402
31.2 IPS |
|
|
Style Transfer (SP)
|
89% |
3642
4.73 IPS |
|
|
Style Transfer (HP)
|
89% |
3316
4.31 IPS |
|
|
Style Transfer (Q)
|
98% |
7856
10.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
849
31.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
852
31.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
667
24.7 IPS |
|
|
Text Classification (SP)
|
100% |
476
635.6 IPS |
|
|
Text Classification (HP)
|
100% |
475
634.4 IPS |
|
|
Text Classification (Q)
|
88% |
881
1.19 KIPS |
|
|
Machine Translation (SP)
|
100% |
717
12.3 IPS |
|
|
Machine Translation (HP)
|
100% |
681
11.7 IPS |
|
|
Machine Translation (Q)
|
50% |
33
1.19 IPS |
