HONOR BKQ-AN20
Geekbench ML Score
328
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 09 2026 06:50 AM |
| Views | 22 |
System Information
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | HONOR BKQ-AN20 |
| Model ID | HONOR BKQ-AN20 |
| Motherboard | BKQ |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm SM8850 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 2 revision 1 |
| Base Frequency | 3.63 GHz |
| Cluster 1 | 6 Cores @ 3.63 GHz |
| Cluster 2 | 2 Cores @ 4.61 GHz |
| Memory Information | |
|---|---|
| Size | 22.58 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1116
208.7 IPS |
|
|
Image Classification (F16)
|
100% |
78
14.6 IPS |
|
|
Image Classification (I8)
|
97% |
85
15.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
322
5.38 IPS |
|
|
Image Segmentation (F16)
|
100% |
320
5.35 IPS |
|
|
Image Segmentation (I8)
|
98% |
332
5.55 IPS |
|
|
Pose Estimation (F32)
|
100% |
1040
1.26 IPS |
|
|
Pose Estimation (F16)
|
100% |
1065
1.29 IPS |
|
|
Pose Estimation (I8)
|
100% |
2900
3.51 IPS |
|
|
Object Detection (F32)
|
100% |
121
9.03 IPS |
|
|
Object Detection (F16)
|
100% |
121
9.04 IPS |
|
|
Object Detection (I8)
|
61% |
139
10.4 IPS |
|
|
Face Detection (F32)
|
100% |
405
4.82 IPS |
|
|
Face Detection (F16)
|
100% |
403
4.80 IPS |
|
|
Face Detection (I8)
|
86% |
465
5.53 IPS |
|
|
Depth Estimation (F32)
|
100% |
422
3.27 IPS |
|
|
Depth Estimation (F16)
|
100% |
419
3.25 IPS |
|
|
Depth Estimation (I8)
|
95% |
486
3.77 IPS |
|
|
Style Transfer (F32)
|
100% |
1842
2.42 IPS |
|
|
Style Transfer (F16)
|
100% |
1879
2.47 IPS |
|
|
Style Transfer (I8)
|
98% |
4178
5.50 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
251
8.96 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
253
9.04 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
314
11.2 IPS |
|
|
Text Classification (F32)
|
100% |
15
21.8 IPS |
|
|
Text Classification (F16)
|
100% |
15
22.1 IPS |
|
|
Text Classification (I8)
|
92% |
17
24.4 IPS |
|
|
Machine Translation (F32)
|
100% |
2635
48.5 IPS |
|
|
Machine Translation (F16)
|
100% |
2414
44.4 IPS |
|
|
Machine Translation (I8)
|
64% |
40
0.73 IPS |
