alps aiv8195p1_64_bsp
Geekbench ML Score
298
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 17 2025 03:16 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | alps aiv8195p1_64_bsp |
| Model ID | alps aiv8195p1_64_bsp |
| Motherboard | aiv8195p1_64_bsp |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 4 Cores @ 2.60 GHz |
| Memory Information | |
|---|---|
| Size | 6.98 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
185
34.5 IPS |
|
|
Image Classification (F16)
|
100% |
286
53.6 IPS |
|
|
Image Classification (I8)
|
97% |
260
48.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
219
3.65 IPS |
|
|
Image Segmentation (F16)
|
100% |
318
5.32 IPS |
|
|
Image Segmentation (I8)
|
98% |
309
5.16 IPS |
|
|
Pose Estimation (F32)
|
100% |
182
0.22 IPS |
|
|
Pose Estimation (F16)
|
100% |
216
0.26 IPS |
|
|
Pose Estimation (I8)
|
100% |
216
0.26 IPS |
|
|
Object Detection (F32)
|
100% |
103
7.66 IPS |
|
|
Object Detection (F16)
|
100% |
153
11.4 IPS |
|
|
Object Detection (I8)
|
62% |
134
9.97 IPS |
|
|
Face Detection (F32)
|
100% |
453
5.38 IPS |
|
|
Face Detection (F16)
|
98% |
556
6.61 IPS |
|
|
Face Detection (I8)
|
86% |
527
6.27 IPS |
|
|
Depth Estimation (F32)
|
100% |
337
2.62 IPS |
|
|
Depth Estimation (F16)
|
100% |
432
3.35 IPS |
|
|
Depth Estimation (I8)
|
95% |
435
3.37 IPS |
|
|
Style Transfer (F32)
|
100% |
708
0.93 IPS |
|
|
Style Transfer (F16)
|
100% |
996
1.31 IPS |
|
|
Style Transfer (I8)
|
98% |
984
1.29 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
178
6.34 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
255
9.11 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
251
8.97 IPS |
|
|
Text Classification (F32)
|
100% |
185
266.4 IPS |
|
|
Text Classification (F16)
|
100% |
185
266.4 IPS |
|
|
Text Classification (I8)
|
92% |
348
500.5 IPS |
|
|
Machine Translation (F32)
|
100% |
350
6.44 IPS |
|
|
Machine Translation (F16)
|
100% |
347
6.38 IPS |
|
|
Machine Translation (I8)
|
64% |
345
6.35 IPS |
