HONOR REA-NX9
Geekbench AI Score
533
Single Precision Score
797
Half Precision Score
697
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | almaspite |
| Upload Date | February 18 2026 01:51 PM |
| Views | 10 |
| Notes | Qualcomm Snapdragon 7 Gen 1 Accelerated Edition |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
389
72.4 IPS |
|
|
Image Classification (HP)
|
100% |
529
98.5 IPS |
|
|
Image Classification (Q)
|
99% |
483
90.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
712
11.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
1124
18.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
778
12.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
2564
2.99 IPS |
|
|
Pose Estimation (HP)
|
99% |
4608
5.38 IPS |
|
|
Pose Estimation (Q)
|
97% |
4492
5.26 IPS |
|
|
Object Detection (SP)
|
100% |
319
25.3 IPS |
|
|
Object Detection (HP)
|
99% |
365
28.9 IPS |
|
|
Object Detection (Q)
|
85% |
364
29.3 IPS |
|
|
Face Detection (SP)
|
100% |
1014
12.0 IPS |
|
|
Face Detection (HP)
|
100% |
1562
18.6 IPS |
|
|
Face Detection (Q)
|
97% |
1109
13.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
1404
10.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
2247
17.4 IPS |
|
|
Depth Estimation (Q)
|
65% |
1870
16.8 IPS |
|
|
Style Transfer (SP)
|
100% |
3194
4.11 IPS |
|
|
Style Transfer (HP)
|
100% |
6542
8.41 IPS |
|
|
Style Transfer (Q)
|
98% |
6362
8.20 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
654
24.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
844
31.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
824
30.5 IPS |
|
|
Text Classification (SP)
|
35% |
16
158.4 IPS |
|
|
Text Classification (HP)
|
35% |
23
207.9 IPS |
|
|
Text Classification (Q)
|
35% |
22
200.6 IPS |
|
|
Machine Translation (SP)
|
100% |
174
2.99 IPS |
|
|
Machine Translation (HP)
|
97% |
234
4.04 IPS |
|
|
Machine Translation (Q)
|
64% |
186
3.82 IPS |
