HONOR FCP-N49
Geekbench AI Score
1854
Single Precision Score
1919
Half Precision Score
2841
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | September 14 2024 01:51 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | HONOR FCP-N49 |
| Model ID | HONOR FCP-N49 |
| Motherboard | FCP |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.30 GHz |
| Memory Information | |
|---|---|
| Size | 11.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1110
206.4 IPS |
|
|
Image Classification (HP)
|
100% |
1535
285.4 IPS |
|
|
Image Classification (Q)
|
100% |
2373
441.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1761
28.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
1756
28.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
2657
43.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
3056
3.57 IPS |
|
|
Pose Estimation (HP)
|
100% |
2853
3.33 IPS |
|
|
Pose Estimation (Q)
|
84% |
6344
7.52 IPS |
|
|
Object Detection (SP)
|
98% |
1332
106.0 IPS |
|
|
Object Detection (HP)
|
98% |
1451
115.4 IPS |
|
|
Object Detection (Q)
|
83% |
1740
140.6 IPS |
|
|
Face Detection (SP)
|
100% |
2745
32.6 IPS |
|
|
Face Detection (HP)
|
100% |
2813
33.4 IPS |
|
|
Face Detection (Q)
|
95% |
4485
53.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
2837
21.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
2812
21.7 IPS |
|
|
Depth Estimation (Q)
|
64% |
4521
41.4 IPS |
|
|
Style Transfer (SP)
|
89% |
7002
9.09 IPS |
|
|
Style Transfer (HP)
|
89% |
7011
9.10 IPS |
|
|
Style Transfer (Q)
|
98% |
13145
17.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1436
53.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1457
53.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3363
124.6 IPS |
|
|
Text Classification (SP)
|
100% |
584
779.0 IPS |
|
|
Text Classification (HP)
|
99% |
619
825.8 IPS |
|
|
Text Classification (Q)
|
88% |
943
1.27 KIPS |
|
|
Machine Translation (SP)
|
100% |
1319
22.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1216
20.9 IPS |
|
|
Machine Translation (Q)
|
50% |
583
20.7 IPS |
