HONOR MBH-N49
Geekbench AI Score
2588
Single Precision Score
3689
Half Precision Score
3169
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | December 22 2025 09:28 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
1717
319.4 IPS |
|
|
Image Classification (HP)
|
100% |
2334
434.1 IPS |
|
|
Image Classification (Q)
|
100% |
2203
409.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
2869
46.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
4943
80.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
5367
87.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
12861
15.0 IPS |
|
|
Pose Estimation (HP)
|
99% |
23091
26.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
22551
26.4 IPS |
|
|
Object Detection (SP)
|
100% |
1520
120.6 IPS |
|
|
Object Detection (HP)
|
99% |
1893
150.2 IPS |
|
|
Object Detection (Q)
|
85% |
1866
150.2 IPS |
|
|
Face Detection (SP)
|
100% |
5084
60.4 IPS |
|
|
Face Detection (HP)
|
100% |
4274
50.8 IPS |
|
|
Face Detection (Q)
|
97% |
3708
44.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
6587
50.7 IPS |
|
|
Depth Estimation (HP)
|
98% |
9020
69.7 IPS |
|
|
Depth Estimation (Q)
|
61% |
7056
68.7 IPS |
|
|
Style Transfer (SP)
|
100% |
16300
21.0 IPS |
|
|
Style Transfer (HP)
|
100% |
35486
45.6 IPS |
|
|
Style Transfer (Q)
|
98% |
34873
45.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3428
126.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5223
192.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5238
194.1 IPS |
|
|
Text Classification (SP)
|
35% |
72
698.8 IPS |
|
|
Text Classification (HP)
|
35% |
73
659.4 IPS |
|
|
Text Classification (Q)
|
33% |
59
665.2 IPS |
|
|
Machine Translation (SP)
|
100% |
1042
17.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1777
30.6 IPS |
|
|
Machine Translation (Q)
|
48% |
729
28.0 IPS |
