HONOR FCP-N49
Geekbench AI Score
2508
Single Precision Score
2562
Half Precision Score
3743
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 21 2024 10:16 PM |
| 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% |
1970
366.4 IPS |
|
|
Image Classification (HP)
|
100% |
2328
432.9 IPS |
|
|
Image Classification (Q)
|
100% |
2608
485.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
2128
34.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2114
34.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
3168
51.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
3921
4.57 IPS |
|
|
Pose Estimation (HP)
|
100% |
3913
4.57 IPS |
|
|
Pose Estimation (Q)
|
84% |
8819
10.5 IPS |
|
|
Object Detection (SP)
|
98% |
1971
156.8 IPS |
|
|
Object Detection (HP)
|
98% |
1767
140.6 IPS |
|
|
Object Detection (Q)
|
83% |
2521
203.6 IPS |
|
|
Face Detection (SP)
|
100% |
3697
43.9 IPS |
|
|
Face Detection (HP)
|
100% |
3673
43.6 IPS |
|
|
Face Detection (Q)
|
95% |
5705
68.1 IPS |
|
|
Depth Estimation (SP)
|
99% |
3874
29.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
3908
30.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
6117
56.0 IPS |
|
|
Style Transfer (SP)
|
89% |
9244
12.0 IPS |
|
|
Style Transfer (HP)
|
89% |
9251
12.0 IPS |
|
|
Style Transfer (Q)
|
98% |
18051
23.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1988
73.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2000
73.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4485
166.2 IPS |
|
|
Text Classification (SP)
|
100% |
797
1.06 KIPS |
|
|
Text Classification (HP)
|
99% |
825
1.10 KIPS |
|
|
Text Classification (Q)
|
88% |
1252
1.69 KIPS |
|
|
Machine Translation (SP)
|
100% |
1454
25.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1636
28.2 IPS |
|
|
Machine Translation (Q)
|
50% |
831
29.5 IPS |
