samsung SM-A566B
Geekbench AI Score
1400
Single Precision Score
1387
Half Precision Score
2899
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | Jockeeth |
| Upload Date | October 15 2025 08:03 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-A566B |
| Model ID | samsung SM-A566B |
| Motherboard | s5e8855 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3457 revision 1 |
| Base Frequency | 1.95 GHz |
| Cluster 1 | 4 Cores @ 1.95 GHz |
| Cluster 2 | 3 Cores @ 2.60 GHz |
| Cluster 3 | 1 Core @ 2.91 GHz |
| Memory Information | |
|---|---|
| Size | 11.13 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1062
197.4 IPS |
|
|
Image Classification (HP)
|
100% |
1090
202.7 IPS |
|
|
Image Classification (Q)
|
100% |
2122
394.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1061
17.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
1009
16.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
2420
39.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
2317
2.70 IPS |
|
|
Pose Estimation (HP)
|
100% |
2337
2.73 IPS |
|
|
Pose Estimation (Q)
|
84% |
6096
7.23 IPS |
|
|
Object Detection (SP)
|
98% |
1062
84.5 IPS |
|
|
Object Detection (HP)
|
98% |
994
79.1 IPS |
|
|
Object Detection (Q)
|
83% |
1958
158.2 IPS |
|
|
Face Detection (SP)
|
100% |
1457
17.3 IPS |
|
|
Face Detection (HP)
|
100% |
1451
17.2 IPS |
|
|
Face Detection (Q)
|
95% |
4765
56.9 IPS |
|
|
Depth Estimation (SP)
|
99% |
2094
16.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
2004
15.5 IPS |
|
|
Depth Estimation (Q)
|
64% |
5242
48.0 IPS |
|
|
Style Transfer (SP)
|
89% |
5396
7.01 IPS |
|
|
Style Transfer (HP)
|
89% |
5466
7.09 IPS |
|
|
Style Transfer (Q)
|
98% |
13809
17.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1048
38.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1080
39.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3301
122.3 IPS |
|
|
Text Classification (SP)
|
100% |
606
808.9 IPS |
|
|
Text Classification (HP)
|
99% |
608
810.9 IPS |
|
|
Text Classification (Q)
|
88% |
1111
1.50 KIPS |
|
|
Machine Translation (SP)
|
100% |
998
17.2 IPS |
|
|
Machine Translation (HP)
|
100% |
991
17.1 IPS |
|
|
Machine Translation (Q)
|
50% |
541
19.2 IPS |
