Samsung Galaxy Note10+ 5G
Geekbench ML Score
526
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 23 2024 01:18 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | Samsung Galaxy Note10+ 5G |
| Model ID | samsung SM-N976V |
| 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 @ 2.84 GHz |
| Memory Information | |
|---|---|
| Size | 11.09 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
257
48.0 IPS |
|
|
Image Classification (F16)
|
100% |
245
45.8 IPS |
|
|
Image Classification (I8)
|
97% |
515
96.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
339
5.67 IPS |
|
|
Image Segmentation (F16)
|
100% |
340
5.68 IPS |
|
|
Image Segmentation (I8)
|
98% |
397
6.63 IPS |
|
|
Pose Estimation (F32)
|
100% |
540
0.65 IPS |
|
|
Pose Estimation (F16)
|
100% |
535
0.65 IPS |
|
|
Pose Estimation (I8)
|
100% |
2538
3.07 IPS |
|
|
Object Detection (F32)
|
100% |
274
20.5 IPS |
|
|
Object Detection (F16)
|
100% |
271
20.2 IPS |
|
|
Object Detection (I8)
|
61% |
722
53.9 IPS |
|
|
Face Detection (F32)
|
100% |
561
6.67 IPS |
|
|
Face Detection (F16)
|
100% |
565
6.71 IPS |
|
|
Face Detection (I8)
|
86% |
1175
14.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
529
4.11 IPS |
|
|
Depth Estimation (F16)
|
100% |
531
4.12 IPS |
|
|
Depth Estimation (I8)
|
95% |
1321
10.2 IPS |
|
|
Style Transfer (F32)
|
100% |
881
1.16 IPS |
|
|
Style Transfer (F16)
|
100% |
897
1.18 IPS |
|
|
Style Transfer (I8)
|
98% |
2390
3.14 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
330
11.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
321
11.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1201
42.9 IPS |
|
|
Text Classification (F32)
|
100% |
317
455.4 IPS |
|
|
Text Classification (F16)
|
100% |
277
398.3 IPS |
|
|
Text Classification (I8)
|
92% |
300
431.0 IPS |
|
|
Machine Translation (F32)
|
100% |
597
11.0 IPS |
|
|
Machine Translation (F16)
|
100% |
576
10.6 IPS |
|
|
Machine Translation (I8)
|
64% |
246
4.52 IPS |
