HONOR MBH-N49
Geekbench AI Score
2657
Single Precision Score
4138
Half Precision Score
3419
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 06 2025 08:45 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm SM8750 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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% |
1641
305.1 IPS |
|
|
Image Classification (HP)
|
100% |
2452
456.0 IPS |
|
|
Image Classification (Q)
|
100% |
2267
421.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
3333
54.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
5786
93.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
5443
88.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
12679
14.8 IPS |
|
|
Pose Estimation (HP)
|
99% |
22972
26.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
22485
26.4 IPS |
|
|
Object Detection (SP)
|
100% |
1517
120.3 IPS |
|
|
Object Detection (HP)
|
99% |
1947
154.4 IPS |
|
|
Object Detection (Q)
|
85% |
1915
154.1 IPS |
|
|
Face Detection (SP)
|
100% |
5387
64.0 IPS |
|
|
Face Detection (HP)
|
100% |
9687
115.1 IPS |
|
|
Face Detection (Q)
|
97% |
8598
102.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6656
51.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
9111
70.4 IPS |
|
|
Depth Estimation (Q)
|
61% |
7048
68.7 IPS |
|
|
Style Transfer (SP)
|
100% |
15910
20.5 IPS |
|
|
Style Transfer (HP)
|
100% |
35220
45.3 IPS |
|
|
Style Transfer (Q)
|
98% |
35180
45.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3470
128.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5587
206.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5397
200.0 IPS |
|
|
Text Classification (SP)
|
35% |
83
812.6 IPS |
|
|
Text Classification (HP)
|
35% |
86
783.4 IPS |
|
|
Text Classification (Q)
|
33% |
61
685.0 IPS |
|
|
Machine Translation (SP)
|
100% |
1016
17.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1556
26.8 IPS |
|
|
Machine Translation (Q)
|
48% |
586
22.5 IPS |
