samsung SM-A065M
Geekbench AI Score
114
Single Precision Score
143
Half Precision Score
112
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 12 2025 12:20 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM MT6769V/CZ |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-A065M |
| Model ID | samsung SM-A065M |
| Motherboard | a06 |
| CPU Information | |
|---|---|
| Name | ARM MT6769V/CZ |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 3 part 3338 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 6 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.00 GHz |
| Memory Information | |
|---|---|
| Size | 3.57 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
95
17.7 IPS |
|
|
Image Classification (HP)
|
100% |
133
24.7 IPS |
|
|
Image Classification (Q)
|
99% |
31
5.74 IPS |
|
|
Image Segmentation (SP)
|
100% |
97
1.57 IPS |
|
|
Image Segmentation (HP)
|
100% |
64
1.04 IPS |
|
|
Image Segmentation (Q)
|
98% |
67
1.08 IPS |
|
|
Pose Estimation (SP)
|
100% |
413
0.48 IPS |
|
|
Pose Estimation (HP)
|
98% |
871
1.02 IPS |
|
|
Pose Estimation (Q)
|
57% |
710
1.17 IPS |
|
|
Object Detection (SP)
|
100% |
85
6.72 IPS |
|
|
Object Detection (HP)
|
100% |
47
3.72 IPS |
|
|
Object Detection (Q)
|
80% |
51
4.17 IPS |
|
|
Face Detection (SP)
|
28% |
16
3.03 IPS |
|
|
Face Detection (HP)
|
100% |
121
1.44 IPS |
|
|
Face Detection (Q)
|
97% |
109
1.30 IPS |
|
|
Depth Estimation (SP)
|
100% |
196
1.51 IPS |
|
|
Depth Estimation (HP)
|
99% |
107
0.83 IPS |
|
|
Depth Estimation (Q)
|
57% |
136
1.48 IPS |
|
|
Style Transfer (SP)
|
100% |
341
0.44 IPS |
|
|
Style Transfer (HP)
|
100% |
209
0.27 IPS |
|
|
Style Transfer (Q)
|
98% |
1111
1.43 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
213
7.86 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
472
17.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
202
7.47 IPS |
|
|
Text Classification (SP)
|
100% |
45
59.8 IPS |
|
|
Text Classification (HP)
|
100% |
69
91.6 IPS |
|
|
Text Classification (Q)
|
93% |
14
18.8 IPS |
|
|
Machine Translation (SP)
|
100% |
118
2.04 IPS |
|
|
Machine Translation (HP)
|
100% |
118
2.04 IPS |
|
|
Machine Translation (Q)
|
57% |
94
2.30 IPS |
