Xiaomi Lenovo TB-9707F
Geekbench ML Score
767
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 21 2024 09:22 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Xiaomi Lenovo TB-9707F |
| Model ID | Xiaomi Lenovo TB-9707F |
| Motherboard | marble |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 2.92 GHz |
| Memory Information | |
|---|---|
| Size | 10.91 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
375
70.1 IPS |
|
|
Image Classification (F16)
|
100% |
374
69.9 IPS |
|
|
Image Classification (I8)
|
97% |
631
118.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
480
8.02 IPS |
|
|
Image Segmentation (F16)
|
100% |
475
7.94 IPS |
|
|
Image Segmentation (I8)
|
98% |
582
9.71 IPS |
|
|
Pose Estimation (F32)
|
100% |
952
1.15 IPS |
|
|
Pose Estimation (F16)
|
100% |
908
1.10 IPS |
|
|
Pose Estimation (I8)
|
100% |
3534
4.28 IPS |
|
|
Object Detection (F32)
|
100% |
343
25.6 IPS |
|
|
Object Detection (F16)
|
100% |
348
26.0 IPS |
|
|
Object Detection (I8)
|
61% |
840
62.7 IPS |
|
|
Face Detection (F32)
|
100% |
842
10.0 IPS |
|
|
Face Detection (F16)
|
100% |
818
9.72 IPS |
|
|
Face Detection (I8)
|
86% |
1417
16.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
923
7.16 IPS |
|
|
Depth Estimation (F16)
|
100% |
921
7.14 IPS |
|
|
Depth Estimation (I8)
|
95% |
1651
12.8 IPS |
|
|
Style Transfer (F32)
|
100% |
1737
2.28 IPS |
|
|
Style Transfer (F16)
|
100% |
1721
2.26 IPS |
|
|
Style Transfer (I8)
|
98% |
4340
5.71 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
537
19.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
548
19.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1499
53.5 IPS |
|
|
Text Classification (F32)
|
100% |
428
614.8 IPS |
|
|
Text Classification (F16)
|
100% |
436
626.4 IPS |
|
|
Text Classification (I8)
|
92% |
311
446.5 IPS |
|
|
Machine Translation (F32)
|
100% |
800
14.7 IPS |
|
|
Machine Translation (F16)
|
100% |
789
14.5 IPS |
|
|
Machine Translation (I8)
|
64% |
352
6.48 IPS |
