HONOR FCP-N49
Geekbench AI Score
1954
Single Precision Score
1977
Half Precision Score
2888
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | September 03 2025 01:05 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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% |
1634
303.8 IPS |
|
|
Image Classification (HP)
|
100% |
1648
306.4 IPS |
|
|
Image Classification (Q)
|
100% |
2218
412.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1815
29.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
1788
29.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
2707
44.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
3293
3.84 IPS |
|
|
Pose Estimation (HP)
|
100% |
3296
3.85 IPS |
|
|
Pose Estimation (Q)
|
84% |
6671
7.91 IPS |
|
|
Object Detection (SP)
|
98% |
1112
88.5 IPS |
|
|
Object Detection (HP)
|
98% |
1462
116.3 IPS |
|
|
Object Detection (Q)
|
83% |
2074
167.5 IPS |
|
|
Face Detection (SP)
|
100% |
2788
33.1 IPS |
|
|
Face Detection (HP)
|
100% |
2870
34.1 IPS |
|
|
Face Detection (Q)
|
95% |
4379
52.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
2893
22.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
2928
22.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
4610
42.2 IPS |
|
|
Style Transfer (SP)
|
89% |
7219
9.37 IPS |
|
|
Style Transfer (HP)
|
89% |
7206
9.35 IPS |
|
|
Style Transfer (Q)
|
98% |
13167
17.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1464
54.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1408
52.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3377
125.1 IPS |
|
|
Text Classification (SP)
|
100% |
628
837.9 IPS |
|
|
Text Classification (HP)
|
99% |
626
836.2 IPS |
|
|
Text Classification (Q)
|
88% |
878
1.18 KIPS |
|
|
Machine Translation (SP)
|
100% |
1399
24.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1207
20.8 IPS |
|
|
Machine Translation (Q)
|
50% |
617
21.9 IPS |
