alps k6989v1_64_pre
Geekbench ML Score
1118
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 15 2024 09:32 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | alps k6989v1_64_pre |
| Model ID | alps k6989v1_64_pre |
| Motherboard | k6989v1_64_pre |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 3 Cores @ 2.85 GHz |
| Cluster 3 | 1 Core @ 3.25 GHz |
| Memory Information | |
|---|---|
| Size | 10.97 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
677
126.7 IPS |
|
|
Image Classification (F16)
|
100% |
712
133.3 IPS |
|
|
Image Classification (I8)
|
97% |
898
168.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
914
15.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
906
15.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
984
16.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
1147
1.39 IPS |
|
|
Pose Estimation (F16)
|
100% |
1088
1.32 IPS |
|
|
Pose Estimation (I8)
|
100% |
4661
5.64 IPS |
|
|
Object Detection (F32)
|
100% |
576
43.0 IPS |
|
|
Object Detection (F16)
|
100% |
613
45.8 IPS |
|
|
Object Detection (I8)
|
61% |
862
64.4 IPS |
|
|
Face Detection (F32)
|
100% |
1461
17.4 IPS |
|
|
Face Detection (F16)
|
100% |
1488
17.7 IPS |
|
|
Face Detection (I8)
|
86% |
1972
23.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1246
9.66 IPS |
|
|
Depth Estimation (F16)
|
100% |
1238
9.60 IPS |
|
|
Depth Estimation (I8)
|
95% |
1767
13.7 IPS |
|
|
Style Transfer (F32)
|
100% |
1926
2.53 IPS |
|
|
Style Transfer (F16)
|
100% |
1893
2.49 IPS |
|
|
Style Transfer (I8)
|
98% |
4341
5.71 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
774
27.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
751
26.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2186
78.1 IPS |
|
|
Text Classification (F32)
|
100% |
729
1.05 KIPS |
|
|
Text Classification (F16)
|
100% |
753
1.08 KIPS |
|
|
Text Classification (I8)
|
92% |
505
725.9 IPS |
|
|
Machine Translation (F32)
|
100% |
1320
24.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1264
23.3 IPS |
|
|
Machine Translation (I8)
|
64% |
427
7.86 IPS |
