HONOR JLH-AN00
Geekbench ML Score
265
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 11 2025 11:01 AM |
| Views | 6 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | HONOR JLH-AN00 |
| Model ID | HONOR JLH-AN00 |
| Motherboard | JLH |
| CPU Information | |
|---|---|
| Name | ARM MT6877V/ZA |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.47 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
159
29.7 IPS |
|
|
Image Classification (F16)
|
100% |
263
49.3 IPS |
|
|
Image Classification (I8)
|
97% |
209
39.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
216
3.61 IPS |
|
|
Image Segmentation (F16)
|
100% |
345
5.76 IPS |
|
|
Image Segmentation (I8)
|
98% |
337
5.64 IPS |
|
|
Pose Estimation (F32)
|
100% |
147
0.18 IPS |
|
|
Pose Estimation (F16)
|
100% |
173
0.21 IPS |
|
|
Pose Estimation (I8)
|
100% |
173
0.21 IPS |
|
|
Object Detection (F32)
|
100% |
100
7.46 IPS |
|
|
Object Detection (F16)
|
100% |
145
10.8 IPS |
|
|
Object Detection (I8)
|
62% |
142
10.6 IPS |
|
|
Face Detection (F32)
|
100% |
469
5.58 IPS |
|
|
Face Detection (F16)
|
98% |
667
7.94 IPS |
|
|
Face Detection (I8)
|
86% |
604
7.18 IPS |
|
|
Depth Estimation (F32)
|
100% |
289
2.24 IPS |
|
|
Depth Estimation (F16)
|
100% |
374
2.90 IPS |
|
|
Depth Estimation (I8)
|
95% |
373
2.89 IPS |
|
|
Style Transfer (F32)
|
100% |
581
0.76 IPS |
|
|
Style Transfer (F16)
|
100% |
819
1.08 IPS |
|
|
Style Transfer (I8)
|
98% |
818
1.08 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
156
5.56 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
241
8.60 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
229
8.18 IPS |
|
|
Text Classification (F32)
|
100% |
139
199.9 IPS |
|
|
Text Classification (F16)
|
100% |
142
204.5 IPS |
|
|
Text Classification (I8)
|
92% |
310
445.6 IPS |
|
|
Machine Translation (F32)
|
100% |
232
4.27 IPS |
|
|
Machine Translation (F16)
|
100% |
236
4.34 IPS |
|
|
Machine Translation (I8)
|
64% |
304
5.59 IPS |
