HONOR MBH-N49
Geekbench AI Score
2632
Single Precision Score
2576
Half Precision Score
4638
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | December 22 2025 09:15 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
2043
379.9 IPS |
|
|
Image Classification (HP)
|
100% |
2136
397.1 IPS |
|
|
Image Classification (Q)
|
100% |
4476
832.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2502
40.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2295
37.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
5310
86.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
4907
5.73 IPS |
|
|
Pose Estimation (HP)
|
100% |
4438
5.18 IPS |
|
|
Pose Estimation (Q)
|
84% |
11553
13.7 IPS |
|
|
Object Detection (SP)
|
98% |
1549
123.2 IPS |
|
|
Object Detection (HP)
|
98% |
1536
122.2 IPS |
|
|
Object Detection (Q)
|
83% |
3639
294.0 IPS |
|
|
Face Detection (SP)
|
100% |
4244
50.4 IPS |
|
|
Face Detection (HP)
|
100% |
4160
49.4 IPS |
|
|
Face Detection (Q)
|
95% |
9083
108.4 IPS |
|
|
Depth Estimation (SP)
|
99% |
4002
30.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
3990
30.8 IPS |
|
|
Depth Estimation (Q)
|
64% |
8167
74.8 IPS |
|
|
Style Transfer (SP)
|
89% |
9928
12.9 IPS |
|
|
Style Transfer (HP)
|
89% |
9708
12.6 IPS |
|
|
Style Transfer (Q)
|
98% |
22354
28.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2022
74.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2040
75.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5427
201.1 IPS |
|
|
Text Classification (SP)
|
100% |
945
1.26 KIPS |
|
|
Text Classification (HP)
|
99% |
941
1.26 KIPS |
|
|
Text Classification (Q)
|
88% |
1015
1.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
1279
22.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1247
21.5 IPS |
|
|
Machine Translation (Q)
|
50% |
505
17.9 IPS |
