BLU B160V
Geekbench AI Score
181
Single Precision Score
182
Half Precision Score
170
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | October 01 2024 03:07 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM MT6761 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | BLU B160V |
| Model ID | BLU B160V |
| Motherboard | B160V |
| CPU Information | |
|---|---|
| Name | ARM MT6761 |
| Topology | 1 Processor, 4 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3331 revision 4 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Memory Information | |
|---|---|
| Size | 2.75 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
84
15.6 IPS |
|
|
Image Classification (HP)
|
100% |
86
16.0 IPS |
|
|
Image Classification (Q)
|
100% |
104
19.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
111
1.81 IPS |
|
|
Image Segmentation (HP)
|
100% |
108
1.76 IPS |
|
|
Image Segmentation (Q)
|
98% |
154
2.50 IPS |
|
|
Pose Estimation (SP)
|
100% |
435
0.51 IPS |
|
|
Pose Estimation (HP)
|
100% |
434
0.51 IPS |
|
|
Pose Estimation (Q)
|
84% |
292
0.35 IPS |
|
|
Object Detection (SP)
|
100% |
91
7.18 IPS |
|
|
Object Detection (HP)
|
100% |
92
7.26 IPS |
|
|
Object Detection (Q)
|
83% |
131
10.6 IPS |
|
|
Face Detection (SP)
|
100% |
224
2.66 IPS |
|
|
Face Detection (HP)
|
100% |
222
2.64 IPS |
|
|
Face Detection (Q)
|
95% |
349
4.17 IPS |
|
|
Depth Estimation (SP)
|
100% |
295
2.27 IPS |
|
|
Depth Estimation (HP)
|
99% |
292
2.25 IPS |
|
|
Depth Estimation (Q)
|
64% |
295
2.70 IPS |
|
|
Style Transfer (SP)
|
89% |
768
1.00 IPS |
|
|
Style Transfer (HP)
|
89% |
741
0.96 IPS |
|
|
Style Transfer (Q)
|
98% |
714
0.92 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
152
5.60 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
156
5.75 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
159
5.89 IPS |
|
|
Text Classification (SP)
|
100% |
93
123.9 IPS |
|
|
Text Classification (HP)
|
100% |
95
126.2 IPS |
|
|
Text Classification (Q)
|
88% |
40
54.0 IPS |
|
|
Machine Translation (SP)
|
100% |
148
2.55 IPS |
|
|
Machine Translation (HP)
|
100% |
152
2.61 IPS |
|
|
Machine Translation (Q)
|
50% |
74
2.64 IPS |
