HONOR MBH-N49
Geekbench AI Score
661
Single Precision Score
660
Half Precision Score
1557
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | December 22 2025 09:25 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm SM8750 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | HONOR MBH-N49 |
| Model ID | HONOR MBH-N49 |
| Motherboard | MBH |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm SM8750 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.32 GHz |
| Memory Information | |
|---|---|
| Size | 14.89 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
425
79.1 IPS |
|
|
Image Classification (HP)
|
100% |
417
77.5 IPS |
|
|
Image Classification (Q)
|
99% |
1149
214.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
534
8.65 IPS |
|
|
Image Segmentation (HP)
|
100% |
530
8.59 IPS |
|
|
Image Segmentation (Q)
|
98% |
1054
17.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
704
0.82 IPS |
|
|
Pose Estimation (HP)
|
100% |
677
0.79 IPS |
|
|
Pose Estimation (Q)
|
98% |
2679
3.14 IPS |
|
|
Object Detection (SP)
|
100% |
372
29.5 IPS |
|
|
Object Detection (HP)
|
100% |
372
29.5 IPS |
|
|
Object Detection (Q)
|
87% |
1127
90.4 IPS |
|
|
Face Detection (SP)
|
100% |
914
10.9 IPS |
|
|
Face Detection (HP)
|
100% |
916
10.9 IPS |
|
|
Face Detection (Q)
|
97% |
2255
26.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
814
6.27 IPS |
|
|
Depth Estimation (HP)
|
99% |
814
6.27 IPS |
|
|
Depth Estimation (Q)
|
64% |
1958
17.8 IPS |
|
|
Style Transfer (SP)
|
100% |
1415
1.82 IPS |
|
|
Style Transfer (HP)
|
100% |
1472
1.89 IPS |
|
|
Style Transfer (Q)
|
98% |
3992
5.15 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
444
16.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
451
16.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1639
60.7 IPS |
|
|
Text Classification (SP)
|
100% |
606
809.4 IPS |
|
|
Text Classification (HP)
|
100% |
618
824.5 IPS |
|
|
Text Classification (Q)
|
91% |
1028
1.38 KIPS |
|
|
Machine Translation (SP)
|
100% |
959
16.5 IPS |
|
|
Machine Translation (HP)
|
100% |
932
16.0 IPS |
|
|
Machine Translation (Q)
|
57% |
774
18.9 IPS |
