HONOR MBH-N49
Geekbench AI Score
2689
Single Precision Score
2605
Half Precision Score
4725
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 06 2025 08:40 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
2050
381.2 IPS |
|
|
Image Classification (HP)
|
100% |
2014
374.5 IPS |
|
|
Image Classification (Q)
|
100% |
4394
817.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
2437
39.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2330
37.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
5191
84.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
4996
5.83 IPS |
|
|
Pose Estimation (HP)
|
100% |
4578
5.34 IPS |
|
|
Pose Estimation (Q)
|
84% |
11401
13.5 IPS |
|
|
Object Detection (SP)
|
98% |
1580
125.7 IPS |
|
|
Object Detection (HP)
|
98% |
1566
124.6 IPS |
|
|
Object Detection (Q)
|
83% |
3663
295.9 IPS |
|
|
Face Detection (SP)
|
100% |
4322
51.4 IPS |
|
|
Face Detection (HP)
|
100% |
4134
49.1 IPS |
|
|
Face Detection (Q)
|
95% |
9364
111.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
4207
32.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
4204
32.5 IPS |
|
|
Depth Estimation (Q)
|
64% |
9065
83.0 IPS |
|
|
Style Transfer (SP)
|
89% |
10257
13.3 IPS |
|
|
Style Transfer (HP)
|
89% |
9993
13.0 IPS |
|
|
Style Transfer (Q)
|
98% |
21041
27.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2207
81.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2181
80.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5907
218.9 IPS |
|
|
Text Classification (SP)
|
100% |
957
1.28 KIPS |
|
|
Text Classification (HP)
|
99% |
907
1.21 KIPS |
|
|
Text Classification (Q)
|
88% |
1033
1.39 KIPS |
|
|
Machine Translation (SP)
|
100% |
1276
22.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1248
21.5 IPS |
|
|
Machine Translation (Q)
|
50% |
535
19.0 IPS |
