HONOR REA-NX9
Geekbench AI Score
197
Single Precision Score
4888
Half Precision Score
13549
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | almaspite |
| Upload Date | February 18 2026 02:21 PM |
| Views | 12 |
| Notes | Qualcomm Snapdragon 7 Gen 1 Accelerated Edition |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | HONOR REA-NX9 |
| Model ID | HONOR REA-NX9 |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3399 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.36 GHz |
| Cluster 3 | 1 Core @ 2.52 GHz |
| Memory Information | |
|---|---|
| Size | 7.14 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
109
20.3 IPS |
|
|
Image Classification (HP)
|
100% |
3370
626.8 IPS |
|
|
Image Classification (Q)
|
99% |
10083
1.88 KIPS |
|
|
Image Segmentation (SP)
|
100% |
155
2.51 IPS |
|
|
Image Segmentation (HP)
|
100% |
2813
45.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
8770
142.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
211
0.25 IPS |
|
|
Pose Estimation (HP)
|
100% |
12472
14.6 IPS |
|
|
Pose Estimation (Q)
|
94% |
53763
63.0 IPS |
|
|
Object Detection (SP)
|
100% |
115
9.13 IPS |
|
|
Object Detection (HP)
|
100% |
2818
223.5 IPS |
|
|
Object Detection (Q)
|
87% |
6785
544.4 IPS |
|
|
Face Detection (SP)
|
100% |
300
3.56 IPS |
|
|
Face Detection (HP)
|
100% |
6841
81.3 IPS |
|
|
Face Detection (Q)
|
97% |
28749
342.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
263
2.03 IPS |
|
|
Depth Estimation (HP)
|
99% |
10280
79.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
28830
264.9 IPS |
|
|
Style Transfer (SP)
|
100% |
456
0.59 IPS |
|
|
Style Transfer (HP)
|
100% |
16579
21.3 IPS |
|
|
Style Transfer (Q)
|
98% |
104629
134.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
128
4.73 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
7772
287.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
23822
882.7 IPS |
|
|
Text Classification (SP)
|
100% |
174
232.7 IPS |
|
|
Text Classification (HP)
|
100% |
2031
2.71 KIPS |
|
|
Text Classification (Q)
|
94% |
4786
6.42 KIPS |
|
|
Machine Translation (SP)
|
100% |
277
4.78 IPS |
|
|
Machine Translation (HP)
|
100% |
1272
21.9 IPS |
|
|
Machine Translation (Q)
|
52% |
654
19.7 IPS |
