HONOR PTP-N49
Geekbench AI Score
1305
Single Precision Score
1277
Half Precision Score
1963
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | y561994 |
| Upload Date | November 28 2025 05:24 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm SM8750 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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 | 10.94 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1774
329.9 IPS |
|
|
Image Classification (HP)
|
100% |
1683
313.0 IPS |
|
|
Image Classification (Q)
|
100% |
1559
289.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
963
15.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
969
15.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
2044
33.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2270
2.65 IPS |
|
|
Pose Estimation (HP)
|
100% |
2299
2.68 IPS |
|
|
Pose Estimation (Q)
|
84% |
5646
6.70 IPS |
|
|
Object Detection (SP)
|
98% |
645
51.3 IPS |
|
|
Object Detection (HP)
|
98% |
711
56.5 IPS |
|
|
Object Detection (Q)
|
83% |
1472
118.9 IPS |
|
|
Face Detection (SP)
|
100% |
2017
24.0 IPS |
|
|
Face Detection (HP)
|
100% |
2086
24.8 IPS |
|
|
Face Detection (Q)
|
95% |
3352
40.0 IPS |
|
|
Depth Estimation (SP)
|
99% |
1990
15.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
1926
14.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
3640
33.3 IPS |
|
|
Style Transfer (SP)
|
89% |
4814
6.25 IPS |
|
|
Style Transfer (HP)
|
89% |
4911
6.38 IPS |
|
|
Style Transfer (Q)
|
98% |
9676
12.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1057
39.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1032
38.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2537
94.0 IPS |
|
|
Text Classification (SP)
|
100% |
428
570.6 IPS |
|
|
Text Classification (HP)
|
99% |
354
473.1 IPS |
|
|
Text Classification (Q)
|
88% |
456
615.0 IPS |
|
|
Machine Translation (SP)
|
100% |
658
11.3 IPS |
|
|
Machine Translation (HP)
|
100% |
601
10.4 IPS |
|
|
Machine Translation (Q)
|
50% |
235
8.33 IPS |
