HONOR MBH-N49
Geekbench AI Score
650
Single Precision Score
28459
Half Precision Score
69441
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | December 22 2025 09:33 PM |
| Views | 16 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| 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% |
419
77.9 IPS |
|
|
Image Classification (HP)
|
100% |
21097
3.92 KIPS |
|
|
Image Classification (Q)
|
96% |
50329
9.40 KIPS |
|
|
Image Segmentation (SP)
|
100% |
499
8.09 IPS |
|
|
Image Segmentation (HP)
|
100% |
13599
220.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
52695
856.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
668
0.78 IPS |
|
|
Pose Estimation (HP)
|
100% |
116691
136.2 IPS |
|
|
Pose Estimation (Q)
|
98% |
480580
562.5 IPS |
|
|
Object Detection (SP)
|
100% |
368
29.2 IPS |
|
|
Object Detection (HP)
|
100% |
20067
1.59 KIPS |
|
|
Object Detection (Q)
|
85% |
30966
2.49 KIPS |
|
|
Face Detection (SP)
|
100% |
952
11.3 IPS |
|
|
Face Detection (HP)
|
100% |
41559
493.8 IPS |
|
|
Face Detection (Q)
|
97% |
151600
1.81 KIPS |
|
|
Depth Estimation (SP)
|
100% |
871
6.71 IPS |
|
|
Depth Estimation (HP)
|
99% |
83687
644.8 IPS |
|
|
Depth Estimation (Q)
|
63% |
177340
1.65 KIPS |
|
|
Style Transfer (SP)
|
100% |
1498
1.93 IPS |
|
|
Style Transfer (HP)
|
100% |
93156
119.8 IPS |
|
|
Style Transfer (Q)
|
98% |
486496
627.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
442
16.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
53883
1.99 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
106912
3.96 KIPS |
|
|
Text Classification (SP)
|
100% |
487
650.4 IPS |
|
|
Text Classification (HP)
|
100% |
4463
5.96 KIPS |
|
|
Text Classification (Q)
|
93% |
11668
15.7 KIPS |
|
|
Machine Translation (SP)
|
100% |
986
17.0 IPS |
|
|
Machine Translation (HP)
|
100% |
6658
114.7 IPS |
|
|
Machine Translation (Q)
|
56% |
4049
104.3 IPS |
