OnePlus 7T
Geekbench ML Score
484
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 23 2024 09:05 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | OnePlus 7T |
| Model ID | OnePlus HD1901 |
| Motherboard | msmnile |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 13 part 2052 revision 14 |
| Base Frequency | 1.78 GHz |
| Cluster 1 | 4 Cores @ 1.79 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 2.96 GHz |
| Memory Information | |
|---|---|
| Size | 7.28 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
234
43.9 IPS |
|
|
Image Classification (F16)
|
100% |
394
73.7 IPS |
|
|
Image Classification (I8)
|
97% |
397
74.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
306
5.11 IPS |
|
|
Image Segmentation (F16)
|
100% |
574
9.59 IPS |
|
|
Image Segmentation (I8)
|
98% |
558
9.32 IPS |
|
|
Pose Estimation (F32)
|
100% |
474
0.57 IPS |
|
|
Pose Estimation (F16)
|
100% |
361
0.44 IPS |
|
|
Pose Estimation (I8)
|
100% |
360
0.44 IPS |
|
|
Object Detection (F32)
|
100% |
204
15.2 IPS |
|
|
Object Detection (F16)
|
100% |
235
17.5 IPS |
|
|
Object Detection (I8)
|
62% |
237
17.7 IPS |
|
|
Face Detection (F32)
|
100% |
551
6.55 IPS |
|
|
Face Detection (F16)
|
97% |
1035
12.3 IPS |
|
|
Face Detection (I8)
|
87% |
1317
15.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
530
4.11 IPS |
|
|
Depth Estimation (F16)
|
100% |
1058
8.21 IPS |
|
|
Depth Estimation (I8)
|
95% |
1067
8.28 IPS |
|
|
Style Transfer (F32)
|
100% |
1099
1.45 IPS |
|
|
Style Transfer (F16)
|
100% |
2621
3.45 IPS |
|
|
Style Transfer (I8)
|
98% |
2613
3.44 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
300
10.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
496
17.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
495
17.7 IPS |
|
|
Text Classification (F32)
|
100% |
203
291.5 IPS |
|
|
Text Classification (F16)
|
100% |
202
291.0 IPS |
|
|
Text Classification (I8)
|
92% |
334
479.9 IPS |
|
|
Machine Translation (F32)
|
100% |
350
6.44 IPS |
|
|
Machine Translation (F16)
|
100% |
354
6.51 IPS |
|
|
Machine Translation (I8)
|
64% |
349
6.41 IPS |
