Xiaomi 23116PN5BC
Geekbench AI Score
509
Single Precision Score
10962
Half Precision Score
30888
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | wudi890 |
| Upload Date | September 10 2024 05:25 PM |
| Views | 17 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Xiaomi 23116PN5BC |
| Model ID | Xiaomi 23116PN5BC |
| Motherboard | shennong |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.30 GHz |
| Memory Information | |
|---|---|
| Size | 14.85 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
320
59.5 IPS |
|
|
Image Classification (HP)
|
100% |
14045
2.61 KIPS |
|
|
Image Classification (Q)
|
97% |
39305
7.33 KIPS |
|
|
Image Segmentation (SP)
|
100% |
392
6.35 IPS |
|
|
Image Segmentation (HP)
|
100% |
8931
144.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
24537
399.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
532
0.62 IPS |
|
|
Pose Estimation (HP)
|
100% |
52113
60.8 IPS |
|
|
Pose Estimation (Q)
|
98% |
277503
324.8 IPS |
|
|
Object Detection (SP)
|
100% |
304
24.1 IPS |
|
|
Object Detection (HP)
|
100% |
11184
887.1 IPS |
|
|
Object Detection (Q)
|
86% |
15669
1.26 KIPS |
|
|
Face Detection (SP)
|
100% |
745
8.85 IPS |
|
|
Face Detection (HP)
|
100% |
25457
302.5 IPS |
|
|
Face Detection (Q)
|
97% |
102310
1.22 KIPS |
|
|
Depth Estimation (SP)
|
100% |
649
5.00 IPS |
|
|
Depth Estimation (HP)
|
99% |
43088
332.0 IPS |
|
|
Depth Estimation (Q)
|
63% |
95811
897.1 IPS |
|
|
Style Transfer (SP)
|
100% |
1036
1.33 IPS |
|
|
Style Transfer (HP)
|
24% |
2147
64.9 IPS |
|
|
Style Transfer (Q)
|
98% |
205395
264.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
350
12.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
22730
839.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
76890
2.85 KIPS |
|
|
Text Classification (SP)
|
100% |
460
614.3 IPS |
|
|
Text Classification (HP)
|
100% |
2170
2.90 KIPS |
|
|
Text Classification (Q)
|
93% |
5295
7.11 KIPS |
|
|
Machine Translation (SP)
|
100% |
726
12.5 IPS |
|
|
Machine Translation (HP)
|
100% |
2953
50.9 IPS |
|
|
Machine Translation (Q)
|
30% |
230
46.3 IPS |
