HONOR NDL-W09
Geekbench AI Score
339
Single Precision Score
342
Half Precision Score
414
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 31 2024 02:39 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | HONOR NDL-W09 |
| Model ID | HONOR NDL-W09 |
| 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 | 3.68 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
164
30.5 IPS |
|
|
Image Classification (HP)
|
100% |
170
31.5 IPS |
|
|
Image Classification (Q)
|
100% |
315
58.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
219
3.55 IPS |
|
|
Image Segmentation (HP)
|
100% |
219
3.55 IPS |
|
|
Image Segmentation (Q)
|
98% |
402
6.54 IPS |
|
|
Pose Estimation (SP)
|
100% |
816
0.95 IPS |
|
|
Pose Estimation (HP)
|
100% |
858
1.00 IPS |
|
|
Pose Estimation (Q)
|
84% |
704
0.83 IPS |
|
|
Object Detection (SP)
|
100% |
168
13.3 IPS |
|
|
Object Detection (HP)
|
100% |
166
13.2 IPS |
|
|
Object Detection (Q)
|
83% |
318
25.7 IPS |
|
|
Face Detection (SP)
|
100% |
462
5.49 IPS |
|
|
Face Detection (HP)
|
100% |
458
5.44 IPS |
|
|
Face Detection (Q)
|
95% |
732
8.74 IPS |
|
|
Depth Estimation (SP)
|
100% |
692
5.33 IPS |
|
|
Depth Estimation (HP)
|
99% |
713
5.49 IPS |
|
|
Depth Estimation (Q)
|
64% |
738
6.76 IPS |
|
|
Style Transfer (SP)
|
89% |
1391
1.81 IPS |
|
|
Style Transfer (HP)
|
89% |
1393
1.81 IPS |
|
|
Style Transfer (Q)
|
98% |
1878
2.42 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
337
12.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
338
12.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
416
15.4 IPS |
|
|
Text Classification (SP)
|
100% |
133
177.0 IPS |
|
|
Text Classification (HP)
|
100% |
132
176.5 IPS |
|
|
Text Classification (Q)
|
88% |
145
195.3 IPS |
|
|
Machine Translation (SP)
|
100% |
210
3.62 IPS |
|
|
Machine Translation (HP)
|
100% |
207
3.57 IPS |
|
|
Machine Translation (Q)
|
50% |
87
3.08 IPS |
