DANEW Konnect 660
Geekbench AI Score
108
Single Precision Score
104
Half Precision Score
75
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | December 16 2025 05:44 PM |
| Views | 14 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | DANEW Konnect 660 |
| Model ID | DANEW Konnect 660 |
| Motherboard | s9863a1h10_go |
| Governor | uscfreq |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3333 revision 0 |
| Base Frequency | 1.20 GHz |
| Cluster 1 | 4 Cores @ 1.20 GHz |
| Cluster 2 | 4 Cores @ 1.60 GHz |
| Memory Information | |
|---|---|
| Size | 2.74 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
63
11.7 IPS |
|
|
Image Classification (HP)
|
100% |
56
10.4 IPS |
|
|
Image Classification (Q)
|
100% |
55
10.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
76
1.23 IPS |
|
|
Image Segmentation (HP)
|
100% |
73
1.18 IPS |
|
|
Image Segmentation (Q)
|
98% |
63
1.02 IPS |
|
|
Pose Estimation (SP)
|
100% |
361
0.42 IPS |
|
|
Pose Estimation (HP)
|
100% |
351
0.41 IPS |
|
|
Pose Estimation (Q)
|
96% |
337
0.39 IPS |
|
|
Object Detection (SP)
|
100% |
60
4.73 IPS |
|
|
Object Detection (HP)
|
100% |
56
4.46 IPS |
|
|
Object Detection (Q)
|
84% |
53
4.24 IPS |
|
|
Face Detection (SP)
|
100% |
206
2.44 IPS |
|
|
Face Detection (HP)
|
100% |
186
2.21 IPS |
|
|
Face Detection (Q)
|
97% |
148
1.77 IPS |
|
|
Depth Estimation (SP)
|
100% |
224
1.73 IPS |
|
|
Depth Estimation (HP)
|
99% |
216
1.67 IPS |
|
|
Depth Estimation (Q)
|
65% |
167
1.51 IPS |
|
|
Style Transfer (SP)
|
100% |
613
0.79 IPS |
|
|
Style Transfer (HP)
|
100% |
593
0.76 IPS |
|
|
Style Transfer (Q)
|
98% |
567
0.73 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
159
5.87 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
161
5.93 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
143
5.31 IPS |
|
|
Text Classification (SP)
|
35% |
8
75.3 IPS |
|
|
Text Classification (HP)
|
35% |
8
74.2 IPS |
|
|
Text Classification (Q)
|
32% |
5
66.3 IPS |
|
|
Machine Translation (SP)
|
100% |
62
1.07 IPS |
|
|
Machine Translation (HP)
|
100% |
61
1.05 IPS |
|
|
Machine Translation (Q)
|
41% |
10
0.70 IPS |
