alps tb8775p1_64_titan_whitesnake_25b
Geekbench ML Score
1664
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 04 2025 08:21 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | alps tb8775p1_64_titan_whitesnake_25b |
| Model ID | alps tb8775p1_64_titan_whitesnake_25b |
| Motherboard | tb8775p1_64_titan_whitesnake_25b |
| 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 @ 2.50 GHz |
| Memory Information | |
|---|---|
| Size | 5.16 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
469
87.7 IPS |
|
|
Image Classification (F16)
|
100% |
1709
319.9 IPS |
|
|
Image Classification (I8)
|
97% |
4680
875.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
589
9.83 IPS |
|
|
Image Segmentation (F16)
|
100% |
1799
30.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
2136
35.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
2899
3.51 IPS |
|
|
Pose Estimation (F16)
|
100% |
4829
5.85 IPS |
|
|
Pose Estimation (I8)
|
100% |
26776
32.4 IPS |
|
|
Object Detection (F32)
|
100% |
337
25.2 IPS |
|
|
Object Detection (F16)
|
100% |
1364
101.8 IPS |
|
|
Object Detection (I8)
|
64% |
1929
144.0 IPS |
|
|
Face Detection (F32)
|
100% |
1462
17.4 IPS |
|
|
Face Detection (F16)
|
97% |
4508
53.6 IPS |
|
|
Face Detection (I8)
|
86% |
9843
117.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
420
3.26 IPS |
|
|
Depth Estimation (F16)
|
100% |
7601
58.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
13863
107.5 IPS |
|
|
Style Transfer (F32)
|
100% |
1697
2.23 IPS |
|
|
Style Transfer (F16)
|
100% |
1596
2.10 IPS |
|
|
Style Transfer (I8)
|
31% |
4464
5.87 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1123
40.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4448
158.8 IPS |
|
|
Image Super-Resolution (I8)
|
33% |
9852
351.8 IPS |
|
|
Text Classification (F32)
|
100% |
67
96.5 IPS |
|
|
Text Classification (F16)
|
100% |
976
1.40 KIPS |
|
|
Text Classification (I8)
|
92% |
1209
1.74 KIPS |
|
|
Machine Translation (F32)
|
100% |
190
3.49 IPS |
|
|
Machine Translation (F16)
|
100% |
188
3.47 IPS |
|
|
Machine Translation (I8)
|
66% |
318
5.85 IPS |
