alps k6989v1_64_pre
Geekbench ML Score
890
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 15 2024 04:43 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
463
86.6 IPS |
|
|
Image Classification (F16)
|
100% |
600
112.2 IPS |
|
|
Image Classification (I8)
|
97% |
568
106.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
1108
18.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1181
19.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
1151
19.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
606
0.73 IPS |
|
|
Pose Estimation (F16)
|
100% |
902
1.09 IPS |
|
|
Pose Estimation (I8)
|
100% |
899
1.09 IPS |
|
|
Object Detection (F32)
|
100% |
400
29.8 IPS |
|
|
Object Detection (F16)
|
100% |
517
38.6 IPS |
|
|
Object Detection (I8)
|
62% |
513
38.3 IPS |
|
|
Face Detection (F32)
|
100% |
2090
24.8 IPS |
|
|
Face Detection (F16)
|
98% |
2253
26.8 IPS |
|
|
Face Detection (I8)
|
86% |
2047
24.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
1243
9.64 IPS |
|
|
Depth Estimation (F16)
|
100% |
1506
11.7 IPS |
|
|
Depth Estimation (I8)
|
95% |
1490
11.6 IPS |
|
|
Style Transfer (F32)
|
100% |
3400
4.47 IPS |
|
|
Style Transfer (F16)
|
100% |
4285
5.64 IPS |
|
|
Style Transfer (I8)
|
98% |
4302
5.66 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
696
24.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
834
29.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
826
29.5 IPS |
|
|
Text Classification (F32)
|
100% |
281
404.1 IPS |
|
|
Text Classification (F16)
|
100% |
283
406.5 IPS |
|
|
Text Classification (I8)
|
92% |
450
647.2 IPS |
|
|
Machine Translation (F32)
|
100% |
456
8.40 IPS |
|
|
Machine Translation (F16)
|
100% |
454
8.35 IPS |
|
|
Machine Translation (I8)
|
64% |
418
7.70 IPS |
