HONOR NDL-L09
Geekbench AI Score
214
Single Precision Score
223
Half Precision Score
231
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | November 29 2024 05:07 PM |
| Views | 28 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | HONOR NDL-L09 |
| Model ID | HONOR NDL-L09 |
| Motherboard | NDL |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3337 revision 0 |
| Base Frequency | 1.90 GHz |
| Cluster 1 | 4 Cores @ 1.90 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 3.62 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
92
17.0 IPS |
|
|
Image Classification (HP)
|
100% |
99
18.4 IPS |
|
|
Image Classification (Q)
|
100% |
153
28.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
136
2.20 IPS |
|
|
Image Segmentation (HP)
|
100% |
138
2.24 IPS |
|
|
Image Segmentation (Q)
|
98% |
195
3.17 IPS |
|
|
Pose Estimation (SP)
|
100% |
438
0.51 IPS |
|
|
Pose Estimation (HP)
|
100% |
472
0.55 IPS |
|
|
Pose Estimation (Q)
|
84% |
313
0.37 IPS |
|
|
Object Detection (SP)
|
100% |
121
9.61 IPS |
|
|
Object Detection (HP)
|
100% |
109
8.63 IPS |
|
|
Object Detection (Q)
|
83% |
153
12.3 IPS |
|
|
Face Detection (SP)
|
100% |
253
3.01 IPS |
|
|
Face Detection (HP)
|
100% |
272
3.23 IPS |
|
|
Face Detection (Q)
|
95% |
348
4.15 IPS |
|
|
Depth Estimation (SP)
|
100% |
384
2.96 IPS |
|
|
Depth Estimation (HP)
|
99% |
389
2.99 IPS |
|
|
Depth Estimation (Q)
|
64% |
374
3.42 IPS |
|
|
Style Transfer (SP)
|
89% |
799
1.04 IPS |
|
|
Style Transfer (HP)
|
89% |
819
1.06 IPS |
|
|
Style Transfer (Q)
|
98% |
893
1.15 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
205
7.57 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
201
7.40 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
194
7.20 IPS |
|
|
Text Classification (SP)
|
100% |
93
124.2 IPS |
|
|
Text Classification (HP)
|
100% |
127
169.6 IPS |
|
|
Text Classification (Q)
|
88% |
143
192.4 IPS |
|
|
Machine Translation (SP)
|
100% |
207
3.57 IPS |
|
|
Machine Translation (HP)
|
100% |
203
3.50 IPS |
|
|
Machine Translation (Q)
|
50% |
96
3.40 IPS |
