samsung SM-A366W
Geekbench AI Score
796
Single Precision Score
852
Half Precision Score
1513
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | April 15 2025 08:36 PM |
| Views | 10 |
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% |
193
35.8 IPS |
|
|
Image Classification (HP)
|
100% |
447
83.2 IPS |
|
|
Image Classification (Q)
|
100% |
1441
267.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
534
8.66 IPS |
|
|
Image Segmentation (HP)
|
100% |
530
8.59 IPS |
|
|
Image Segmentation (Q)
|
98% |
1659
27.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
2038
2.38 IPS |
|
|
Pose Estimation (HP)
|
100% |
2011
2.35 IPS |
|
|
Pose Estimation (Q)
|
84% |
3764
4.46 IPS |
|
|
Object Detection (SP)
|
100% |
456
36.2 IPS |
|
|
Object Detection (HP)
|
100% |
440
34.9 IPS |
|
|
Object Detection (Q)
|
83% |
1269
102.5 IPS |
|
|
Face Detection (SP)
|
100% |
1137
13.5 IPS |
|
|
Face Detection (HP)
|
100% |
1132
13.4 IPS |
|
|
Face Detection (Q)
|
95% |
3371
40.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
825
6.36 IPS |
|
|
Depth Estimation (HP)
|
99% |
809
6.24 IPS |
|
|
Depth Estimation (Q)
|
64% |
3410
31.2 IPS |
|
|
Style Transfer (SP)
|
89% |
3662
4.75 IPS |
|
|
Style Transfer (HP)
|
89% |
3515
4.56 IPS |
|
|
Style Transfer (Q)
|
98% |
7563
9.75 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
877
32.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
867
32.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2029
75.2 IPS |
|
|
Text Classification (SP)
|
100% |
494
659.9 IPS |
|
|
Text Classification (HP)
|
100% |
490
653.9 IPS |
|
|
Text Classification (Q)
|
88% |
919
1.24 KIPS |
|
|
Machine Translation (SP)
|
100% |
717
12.4 IPS |
|
|
Machine Translation (HP)
|
100% |
705
12.1 IPS |
|
|
Machine Translation (Q)
|
50% |
34
1.22 IPS |
