HONOR AGT-AN00
Geekbench ML Score
744
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | December 29 2024 10:38 AM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | HONOR AGT-AN00 |
| Model ID | HONOR AGT-AN00 |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM SM8475 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 3.00 GHz |
| Memory Information | |
|---|---|
| Size | 11.03 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
327
61.2 IPS |
|
|
Image Classification (F16)
|
100% |
369
69.0 IPS |
|
|
Image Classification (I8)
|
97% |
521
97.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
463
7.72 IPS |
|
|
Image Segmentation (F16)
|
100% |
481
8.04 IPS |
|
|
Image Segmentation (I8)
|
98% |
585
9.77 IPS |
|
|
Pose Estimation (F32)
|
100% |
858
1.04 IPS |
|
|
Pose Estimation (F16)
|
100% |
813
0.98 IPS |
|
|
Pose Estimation (I8)
|
100% |
3474
4.21 IPS |
|
|
Object Detection (F32)
|
100% |
355
26.5 IPS |
|
|
Object Detection (F16)
|
100% |
320
23.9 IPS |
|
|
Object Detection (I8)
|
61% |
838
62.6 IPS |
|
|
Face Detection (F32)
|
100% |
831
9.88 IPS |
|
|
Face Detection (F16)
|
100% |
828
9.84 IPS |
|
|
Face Detection (I8)
|
86% |
1415
16.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
918
7.12 IPS |
|
|
Depth Estimation (F16)
|
100% |
895
6.94 IPS |
|
|
Depth Estimation (I8)
|
95% |
1916
14.9 IPS |
|
|
Style Transfer (F32)
|
100% |
1691
2.22 IPS |
|
|
Style Transfer (F16)
|
100% |
1639
2.16 IPS |
|
|
Style Transfer (I8)
|
98% |
3426
4.51 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
518
18.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
536
19.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1344
48.0 IPS |
|
|
Text Classification (F32)
|
100% |
426
612.1 IPS |
|
|
Text Classification (F16)
|
100% |
425
611.5 IPS |
|
|
Text Classification (I8)
|
92% |
320
460.5 IPS |
|
|
Machine Translation (F32)
|
100% |
796
14.7 IPS |
|
|
Machine Translation (F16)
|
100% |
765
14.1 IPS |
|
|
Machine Translation (I8)
|
64% |
388
7.14 IPS |
