HONOR REA-NX9
Geekbench AI Score
883
Single Precision Score
1606
Half Precision Score
2323
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | almaspite |
| Upload Date | February 18 2026 01:45 PM |
| Views | 11 |
| Notes | Qualcomm Snapdragon 7 Gen 1 Accelerated Edition |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
463
86.1 IPS |
|
|
Image Classification (HP)
|
100% |
942
175.1 IPS |
|
|
Image Classification (Q)
|
99% |
1764
328.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
549
8.90 IPS |
|
|
Image Segmentation (HP)
|
100% |
1021
16.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
1988
32.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
2016
2.35 IPS |
|
|
Pose Estimation (HP)
|
92% |
4004
4.70 IPS |
|
|
Pose Estimation (Q)
|
96% |
4886
5.73 IPS |
|
|
Object Detection (SP)
|
100% |
417
33.1 IPS |
|
|
Object Detection (HP)
|
97% |
844
67.2 IPS |
|
|
Object Detection (Q)
|
85% |
1362
109.8 IPS |
|
|
Face Detection (SP)
|
100% |
1061
12.6 IPS |
|
|
Face Detection (HP)
|
100% |
2031
24.1 IPS |
|
|
Face Detection (Q)
|
97% |
3715
44.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
1577
12.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
3071
23.7 IPS |
|
|
Depth Estimation (Q)
|
64% |
3526
32.5 IPS |
|
|
Style Transfer (SP)
|
89% |
3383
4.39 IPS |
|
|
Style Transfer (HP)
|
88% |
4615
5.99 IPS |
|
|
Style Transfer (Q)
|
98% |
10296
13.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
829
30.6 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
1771
65.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2593
96.1 IPS |
|
|
Text Classification (SP)
|
100% |
481
642.6 IPS |
|
|
Text Classification (HP)
|
100% |
782
1.04 KIPS |
|
|
Text Classification (Q)
|
93% |
814
1.09 KIPS |
|
|
Machine Translation (SP)
|
100% |
598
10.3 IPS |
|
|
Machine Translation (HP)
|
96% |
885
15.3 IPS |
|
|
Machine Translation (Q)
|
55% |
690
18.5 IPS |
