alps tb8775p1_64_titan_whitesnake_25b
Geekbench ML Score
1648
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 04 2025 04:47 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% |
466
87.3 IPS |
|
|
Image Classification (F16)
|
100% |
1706
319.3 IPS |
|
|
Image Classification (I8)
|
97% |
4746
888.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
590
9.86 IPS |
|
|
Image Segmentation (F16)
|
100% |
1802
30.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
2149
35.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
2879
3.49 IPS |
|
|
Pose Estimation (F16)
|
100% |
4852
5.88 IPS |
|
|
Pose Estimation (I8)
|
100% |
26765
32.4 IPS |
|
|
Object Detection (F32)
|
100% |
334
25.0 IPS |
|
|
Object Detection (F16)
|
100% |
1118
83.4 IPS |
|
|
Object Detection (I8)
|
64% |
1944
145.2 IPS |
|
|
Face Detection (F32)
|
100% |
1465
17.4 IPS |
|
|
Face Detection (F16)
|
97% |
4516
53.7 IPS |
|
|
Face Detection (I8)
|
86% |
9921
118.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
419
3.25 IPS |
|
|
Depth Estimation (F16)
|
100% |
7605
59.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
13154
102.0 IPS |
|
|
Style Transfer (F32)
|
100% |
1697
2.23 IPS |
|
|
Style Transfer (F16)
|
100% |
1590
2.09 IPS |
|
|
Style Transfer (I8)
|
31% |
4468
5.88 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1121
40.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4426
158.0 IPS |
|
|
Image Super-Resolution (I8)
|
33% |
9478
338.5 IPS |
|
|
Text Classification (F32)
|
100% |
67
96.8 IPS |
|
|
Text Classification (F16)
|
100% |
985
1.42 KIPS |
|
|
Text Classification (I8)
|
92% |
1196
1.72 KIPS |
|
|
Machine Translation (F32)
|
100% |
190
3.50 IPS |
|
|
Machine Translation (F16)
|
100% |
188
3.45 IPS |
|
|
Machine Translation (I8)
|
66% |
317
5.83 IPS |
