HONOR AGT-AN00
Geekbench ML Score
853
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | December 29 2024 10:35 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
550
103.0 IPS |
|
|
Image Classification (F16)
|
100% |
566
105.8 IPS |
|
|
Image Classification (I8)
|
97% |
476
89.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
858
14.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1205
20.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
1068
17.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
724
0.88 IPS |
|
|
Pose Estimation (F16)
|
100% |
1292
1.56 IPS |
|
|
Pose Estimation (I8)
|
100% |
1304
1.58 IPS |
|
|
Object Detection (F32)
|
100% |
241
18.0 IPS |
|
|
Object Detection (F16)
|
100% |
250
18.7 IPS |
|
|
Object Detection (I8)
|
62% |
236
17.6 IPS |
|
|
Face Detection (F32)
|
100% |
1580
18.8 IPS |
|
|
Face Detection (F16)
|
97% |
2332
27.7 IPS |
|
|
Face Detection (I8)
|
87% |
1568
18.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
1135
8.80 IPS |
|
|
Depth Estimation (F16)
|
100% |
2668
20.7 IPS |
|
|
Depth Estimation (I8)
|
95% |
2614
20.3 IPS |
|
|
Style Transfer (F32)
|
100% |
2912
3.83 IPS |
|
|
Style Transfer (F16)
|
100% |
6475
8.52 IPS |
|
|
Style Transfer (I8)
|
98% |
6642
8.74 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
398
14.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
537
19.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
531
18.9 IPS |
|
|
Text Classification (F32)
|
100% |
269
386.2 IPS |
|
|
Text Classification (F16)
|
100% |
268
385.7 IPS |
|
|
Text Classification (I8)
|
92% |
487
700.1 IPS |
|
|
Machine Translation (F32)
|
100% |
473
8.71 IPS |
|
|
Machine Translation (F16)
|
100% |
475
8.75 IPS |
|
|
Machine Translation (I8)
|
64% |
593
10.9 IPS |
