Realme GT Neo
Geekbench ML Score
621
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 06:23 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Realme GT Neo |
| Model ID | realme RMX3031 |
| Motherboard | RM6893 |
| CPU Information | |
|---|---|
| Name | ARM MT6893Z/CZA |
| 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 | 3 Cores @ 2.60 GHz |
| Cluster 3 | 1 Core @ 3.00 GHz |
| Memory Information | |
|---|---|
| Size | 11.25 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
295
55.1 IPS |
|
|
Image Classification (F16)
|
100% |
287
53.7 IPS |
|
|
Image Classification (I8)
|
97% |
655
122.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
338
5.65 IPS |
|
|
Image Segmentation (F16)
|
100% |
331
5.52 IPS |
|
|
Image Segmentation (I8)
|
98% |
497
8.30 IPS |
|
|
Pose Estimation (F32)
|
100% |
621
0.75 IPS |
|
|
Pose Estimation (F16)
|
100% |
630
0.76 IPS |
|
|
Pose Estimation (I8)
|
100% |
2856
3.46 IPS |
|
|
Object Detection (F32)
|
100% |
318
23.8 IPS |
|
|
Object Detection (F16)
|
100% |
303
22.6 IPS |
|
|
Object Detection (I8)
|
61% |
788
58.8 IPS |
|
|
Face Detection (F32)
|
100% |
626
7.44 IPS |
|
|
Face Detection (F16)
|
100% |
611
7.26 IPS |
|
|
Face Detection (I8)
|
86% |
1449
17.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
641
4.97 IPS |
|
|
Depth Estimation (F16)
|
100% |
671
5.20 IPS |
|
|
Depth Estimation (I8)
|
95% |
1546
12.0 IPS |
|
|
Style Transfer (F32)
|
100% |
1219
1.60 IPS |
|
|
Style Transfer (F16)
|
100% |
1210
1.59 IPS |
|
|
Style Transfer (I8)
|
98% |
2862
3.76 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
387
13.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
413
14.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1234
44.1 IPS |
|
|
Text Classification (F32)
|
100% |
349
501.8 IPS |
|
|
Text Classification (F16)
|
100% |
321
461.9 IPS |
|
|
Text Classification (I8)
|
92% |
396
569.5 IPS |
|
|
Machine Translation (F32)
|
100% |
753
13.9 IPS |
|
|
Machine Translation (F16)
|
100% |
792
14.6 IPS |
|
|
Machine Translation (I8)
|
64% |
294
5.41 IPS |
