alps k6991v1_64
Geekbench ML Score
4127
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 21 2025 08:16 AM |
| Views | 10 |
System Information
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | alps k6991v1_64 |
| Model ID | alps k6991v1_64 |
| Motherboard | k6991v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3461 revision 0 |
| Base Frequency | 2.10 GHz |
| Cluster 1 | 4 Cores @ 2.10 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 3.10 GHz |
| Memory Information | |
|---|---|
| Size | 10.76 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
804
150.4 IPS |
|
|
Image Classification (F16)
|
100% |
3504
655.7 IPS |
|
|
Image Classification (I8)
|
97% |
10740
2.01 KIPS |
|
|
Image Segmentation (F32)
|
100% |
732
12.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
4152
69.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
2032
33.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
9961
12.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
20579
24.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
83648
101.3 IPS |
|
|
Object Detection (F32)
|
100% |
677
50.5 IPS |
|
|
Object Detection (F16)
|
100% |
3391
253.1 IPS |
|
|
Object Detection (I8)
|
64% |
3789
282.9 IPS |
|
|
Face Detection (F32)
|
100% |
3555
42.3 IPS |
|
|
Face Detection (F16)
|
97% |
14702
174.8 IPS |
|
|
Face Detection (I8)
|
86% |
15556
185.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
437
3.39 IPS |
|
|
Depth Estimation (F16)
|
100% |
21989
170.5 IPS |
|
|
Depth Estimation (I8)
|
95% |
45515
353.0 IPS |
|
|
Style Transfer (F32)
|
100% |
1667
2.19 IPS |
|
|
Style Transfer (F16)
|
100% |
53832
70.8 IPS |
|
|
Style Transfer (I8)
|
98% |
170799
224.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2864
102.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
12175
434.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
32195
1.15 KIPS |
|
|
Text Classification (F32)
|
100% |
95
136.6 IPS |
|
|
Text Classification (F16)
|
100% |
2041
2.93 KIPS |
|
|
Text Classification (I8)
|
92% |
1935
2.78 KIPS |
|
|
Machine Translation (F32)
|
100% |
211
3.88 IPS |
|
|
Machine Translation (F16)
|
100% |
711
13.1 IPS |
|
|
Machine Translation (I8)
|
76% |
309
5.68 IPS |
