Xiaomi 23117RK66C
Geekbench ML Score
1276
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 04 2024 07:46 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Xiaomi 23117RK66C |
| Model ID | Xiaomi 23117RK66C |
| Motherboard | manet |
| 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 |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
631
118.0 IPS |
|
|
Image Classification (F16)
|
100% |
620
116.1 IPS |
|
|
Image Classification (I8)
|
97% |
1078
201.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
825
13.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
788
13.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
933
15.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
1378
1.67 IPS |
|
|
Pose Estimation (F16)
|
100% |
1394
1.69 IPS |
|
|
Pose Estimation (I8)
|
100% |
5728
6.94 IPS |
|
|
Object Detection (F32)
|
100% |
642
47.9 IPS |
|
|
Object Detection (F16)
|
100% |
650
48.5 IPS |
|
|
Object Detection (I8)
|
61% |
1416
105.7 IPS |
|
|
Face Detection (F32)
|
100% |
1431
17.0 IPS |
|
|
Face Detection (F16)
|
100% |
1444
17.2 IPS |
|
|
Face Detection (I8)
|
86% |
2537
30.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
1403
10.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
1400
10.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
2551
19.8 IPS |
|
|
Style Transfer (F32)
|
100% |
2465
3.24 IPS |
|
|
Style Transfer (F16)
|
100% |
2511
3.30 IPS |
|
|
Style Transfer (I8)
|
98% |
5649
7.43 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
975
34.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
998
35.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2658
94.9 IPS |
|
|
Text Classification (F32)
|
100% |
756
1.09 KIPS |
|
|
Text Classification (F16)
|
100% |
754
1.08 KIPS |
|
|
Text Classification (I8)
|
92% |
495
711.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1624
29.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1517
27.9 IPS |
|
|
Machine Translation (I8)
|
64% |
551
10.1 IPS |
