realme RMX3997
Geekbench ML Score
409
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 01 2024 08:31 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | realme RMX3997 |
| Model ID | realme RMX3997 |
| Motherboard | k6835v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.20 GHz |
| Memory Information | |
|---|---|
| Size | 7.45 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
172
32.1 IPS |
|
|
Image Classification (F16)
|
100% |
177
33.1 IPS |
|
|
Image Classification (I8)
|
97% |
339
63.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
291
4.86 IPS |
|
|
Image Segmentation (F16)
|
100% |
292
4.87 IPS |
|
|
Image Segmentation (I8)
|
98% |
415
6.93 IPS |
|
|
Pose Estimation (F32)
|
100% |
390
0.47 IPS |
|
|
Pose Estimation (F16)
|
100% |
391
0.47 IPS |
|
|
Pose Estimation (I8)
|
100% |
1861
2.25 IPS |
|
|
Object Detection (F32)
|
100% |
229
17.1 IPS |
|
|
Object Detection (F16)
|
100% |
228
17.0 IPS |
|
|
Object Detection (I8)
|
61% |
494
36.9 IPS |
|
|
Face Detection (F32)
|
100% |
435
5.17 IPS |
|
|
Face Detection (F16)
|
100% |
435
5.17 IPS |
|
|
Face Detection (I8)
|
86% |
933
11.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
423
3.28 IPS |
|
|
Depth Estimation (F16)
|
100% |
423
3.28 IPS |
|
|
Depth Estimation (I8)
|
95% |
972
7.54 IPS |
|
|
Style Transfer (F32)
|
100% |
660
0.87 IPS |
|
|
Style Transfer (F16)
|
100% |
662
0.87 IPS |
|
|
Style Transfer (I8)
|
98% |
1991
2.62 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
248
8.86 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
249
8.90 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
723
25.8 IPS |
|
|
Text Classification (F32)
|
100% |
256
367.5 IPS |
|
|
Text Classification (F16)
|
100% |
251
360.3 IPS |
|
|
Text Classification (I8)
|
92% |
196
282.1 IPS |
|
|
Machine Translation (F32)
|
100% |
418
7.69 IPS |
|
|
Machine Translation (F16)
|
100% |
411
7.56 IPS |
|
|
Machine Translation (I8)
|
64% |
332
6.10 IPS |
