alps tb8775p1_64_titan_whitesnake_25b
Geekbench ML Score
434
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 03 2025 02:12 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
162
30.3 IPS |
|
|
Image Classification (F16)
|
100% |
170
31.8 IPS |
|
|
Image Classification (I8)
|
97% |
340
63.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
308
5.14 IPS |
|
|
Image Segmentation (F16)
|
100% |
305
5.10 IPS |
|
|
Image Segmentation (I8)
|
98% |
495
8.26 IPS |
|
|
Pose Estimation (F32)
|
100% |
488
0.59 IPS |
|
|
Pose Estimation (F16)
|
100% |
474
0.57 IPS |
|
|
Pose Estimation (I8)
|
100% |
2133
2.58 IPS |
|
|
Object Detection (F32)
|
100% |
202
15.0 IPS |
|
|
Object Detection (F16)
|
100% |
198
14.8 IPS |
|
|
Object Detection (I8)
|
61% |
425
31.7 IPS |
|
|
Face Detection (F32)
|
100% |
479
5.70 IPS |
|
|
Face Detection (F16)
|
100% |
478
5.69 IPS |
|
|
Face Detection (I8)
|
86% |
1004
11.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
470
3.65 IPS |
|
|
Depth Estimation (F16)
|
100% |
466
3.61 IPS |
|
|
Depth Estimation (I8)
|
95% |
1034
8.02 IPS |
|
|
Style Transfer (F32)
|
100% |
885
1.16 IPS |
|
|
Style Transfer (F16)
|
100% |
892
1.17 IPS |
|
|
Style Transfer (I8)
|
98% |
2681
3.53 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
256
9.16 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
268
9.58 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
834
29.8 IPS |
|
|
Text Classification (F32)
|
100% |
222
319.5 IPS |
|
|
Text Classification (F16)
|
100% |
229
329.6 IPS |
|
|
Text Classification (I8)
|
92% |
224
321.7 IPS |
|
|
Machine Translation (F32)
|
100% |
437
8.05 IPS |
|
|
Machine Translation (F16)
|
100% |
432
7.95 IPS |
|
|
Machine Translation (I8)
|
64% |
275
5.06 IPS |
