HONOR FCP-N49
Geekbench AI Score
2219
Single Precision Score
2209
Half Precision Score
3261
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | January 04 2025 01:16 AM |
| Views | 2 |
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% |
1593
296.3 IPS |
|
|
Image Classification (HP)
|
100% |
1933
359.5 IPS |
|
|
Image Classification (Q)
|
100% |
2602
483.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
2117
34.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2102
34.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
3220
52.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
3883
4.53 IPS |
|
|
Pose Estimation (HP)
|
100% |
3279
3.83 IPS |
|
|
Pose Estimation (Q)
|
84% |
7371
8.74 IPS |
|
|
Object Detection (SP)
|
98% |
1657
131.9 IPS |
|
|
Object Detection (HP)
|
98% |
1504
119.7 IPS |
|
|
Object Detection (Q)
|
83% |
2129
171.9 IPS |
|
|
Face Detection (SP)
|
100% |
3081
36.6 IPS |
|
|
Face Detection (HP)
|
100% |
3231
38.4 IPS |
|
|
Face Detection (Q)
|
95% |
5073
60.6 IPS |
|
|
Depth Estimation (SP)
|
99% |
3244
25.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
3321
25.7 IPS |
|
|
Depth Estimation (Q)
|
64% |
5177
47.4 IPS |
|
|
Style Transfer (SP)
|
89% |
8022
10.4 IPS |
|
|
Style Transfer (HP)
|
89% |
8023
10.4 IPS |
|
|
Style Transfer (Q)
|
98% |
14855
19.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1641
60.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1603
59.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3813
141.3 IPS |
|
|
Text Classification (SP)
|
100% |
672
897.0 IPS |
|
|
Text Classification (HP)
|
99% |
671
895.2 IPS |
|
|
Text Classification (Q)
|
88% |
1000
1.35 KIPS |
|
|
Machine Translation (SP)
|
100% |
1513
26.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1496
25.8 IPS |
|
|
Machine Translation (Q)
|
50% |
697
24.7 IPS |
