HONOR PTP-N49
Geekbench AI Score
2500
Single Precision Score
2509
Half Precision Score
4577
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | DDD_Xleb |
| Upload Date | September 25 2025 08:39 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm SM8750 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | HONOR PTP-N49 |
| Model ID | HONOR PTP-N49 |
| Motherboard | PTP |
| 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 | 10.98 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1708
317.7 IPS |
|
|
Image Classification (HP)
|
100% |
2076
386.1 IPS |
|
|
Image Classification (Q)
|
100% |
4271
794.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2366
38.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
2257
36.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
5190
84.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
4724
5.51 IPS |
|
|
Pose Estimation (HP)
|
100% |
4378
5.11 IPS |
|
|
Pose Estimation (Q)
|
84% |
10849
12.9 IPS |
|
|
Object Detection (SP)
|
98% |
1449
115.3 IPS |
|
|
Object Detection (HP)
|
98% |
1490
118.5 IPS |
|
|
Object Detection (Q)
|
83% |
3541
286.0 IPS |
|
|
Face Detection (SP)
|
100% |
3857
45.8 IPS |
|
|
Face Detection (HP)
|
100% |
3902
46.4 IPS |
|
|
Face Detection (Q)
|
95% |
8718
104.1 IPS |
|
|
Depth Estimation (SP)
|
99% |
3868
29.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
3834
29.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
8637
79.1 IPS |
|
|
Style Transfer (SP)
|
89% |
9993
13.0 IPS |
|
|
Style Transfer (HP)
|
89% |
9594
12.5 IPS |
|
|
Style Transfer (Q)
|
98% |
21468
27.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2028
74.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2046
75.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5779
214.2 IPS |
|
|
Text Classification (SP)
|
100% |
907
1.21 KIPS |
|
|
Text Classification (HP)
|
99% |
899
1.20 KIPS |
|
|
Text Classification (Q)
|
88% |
1001
1.35 KIPS |
|
|
Machine Translation (SP)
|
100% |
1261
21.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1228
21.1 IPS |
|
|
Machine Translation (Q)
|
50% |
507
18.0 IPS |
