iPhone XR
Geekbench ML Score
701
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | April 26 2024 09:23 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| Model | iPhone XR |
| Model ID | iPhone11,8 |
| Motherboard | N841AP |
| CPU Information | |
|---|---|
| Name | Apple A12 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 2.49 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 48.0 KB x 1 |
| L1 Data Cache | 32.0 KB x 1 |
| L2 Cache | 2.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 2.77 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
355
66.4 IPS |
|
|
Image Classification (F16)
|
100% |
543
101.7 IPS |
|
|
Image Classification (I8)
|
99% |
535
100.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
236
3.95 IPS |
|
|
Image Segmentation (F16)
|
100% |
285
4.77 IPS |
|
|
Image Segmentation (I8)
|
100% |
282
4.71 IPS |
|
|
Pose Estimation (F32)
|
100% |
931
1.13 IPS |
|
|
Pose Estimation (F16)
|
100% |
1099
1.33 IPS |
|
|
Pose Estimation (I8)
|
100% |
887
1.07 IPS |
|
|
Object Detection (F32)
|
100% |
297
22.2 IPS |
|
|
Object Detection (F16)
|
100% |
575
42.9 IPS |
|
|
Object Detection (I8)
|
97% |
323
24.1 IPS |
|
|
Face Detection (F32)
|
100% |
716
8.51 IPS |
|
|
Face Detection (F16)
|
97% |
1204
14.3 IPS |
|
|
Face Detection (I8)
|
96% |
1230
14.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
771
5.98 IPS |
|
|
Depth Estimation (F16)
|
100% |
1401
10.9 IPS |
|
|
Depth Estimation (I8)
|
99% |
1700
13.2 IPS |
|
|
Style Transfer (F32)
|
100% |
2507
3.30 IPS |
|
|
Style Transfer (F16)
|
100% |
4365
5.74 IPS |
|
|
Style Transfer (I8)
|
100% |
4332
5.70 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
725
25.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
959
34.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
954
34.1 IPS |
|
|
Text Classification (F32)
|
100% |
265
380.6 IPS |
|
|
Text Classification (F16)
|
100% |
514
738.6 IPS |
|
|
Text Classification (I8)
|
96% |
516
741.5 IPS |
|
|
Machine Translation (F32)
|
100% |
341
6.28 IPS |
|
|
Machine Translation (F16)
|
100% |
483
8.88 IPS |
|
|
Machine Translation (I8)
|
99% |
344
6.33 IPS |
