alps tb8775p1_64_titan_whitesnake_25b
Geekbench ML Score
312
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 03 2025 03:15 AM |
| Views | 1 |
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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
178
33.2 IPS |
|
|
Image Classification (F16)
|
100% |
237
44.4 IPS |
|
|
Image Classification (I8)
|
97% |
205
38.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
367
6.14 IPS |
|
|
Image Segmentation (F16)
|
100% |
428
7.15 IPS |
|
|
Image Segmentation (I8)
|
98% |
405
6.76 IPS |
|
|
Pose Estimation (F32)
|
100% |
184
0.22 IPS |
|
|
Pose Estimation (F16)
|
100% |
245
0.30 IPS |
|
|
Pose Estimation (I8)
|
100% |
244
0.30 IPS |
|
|
Object Detection (F32)
|
100% |
161
12.0 IPS |
|
|
Object Detection (F16)
|
100% |
206
15.4 IPS |
|
|
Object Detection (I8)
|
62% |
208
15.5 IPS |
|
|
Face Detection (F32)
|
100% |
683
8.12 IPS |
|
|
Face Detection (F16)
|
98% |
761
9.05 IPS |
|
|
Face Detection (I8)
|
86% |
726
8.64 IPS |
|
|
Depth Estimation (F32)
|
100% |
382
2.96 IPS |
|
|
Depth Estimation (F16)
|
100% |
479
3.71 IPS |
|
|
Depth Estimation (I8)
|
95% |
471
3.66 IPS |
|
|
Style Transfer (F32)
|
100% |
978
1.29 IPS |
|
|
Style Transfer (F16)
|
100% |
1159
1.52 IPS |
|
|
Style Transfer (I8)
|
98% |
1153
1.52 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
220
7.85 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
249
8.90 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
247
8.82 IPS |
|
|
Text Classification (F32)
|
100% |
105
150.4 IPS |
|
|
Text Classification (F16)
|
100% |
104
149.0 IPS |
|
|
Text Classification (I8)
|
92% |
268
384.9 IPS |
|
|
Machine Translation (F32)
|
100% |
184
3.38 IPS |
|
|
Machine Translation (F16)
|
100% |
184
3.39 IPS |
|
|
Machine Translation (I8)
|
64% |
287
5.28 IPS |
