iPhone XR
Geekbench ML Score
699
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 07 2024 09:58 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5 |
| 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% |
354
66.2 IPS |
|
|
Image Classification (F16)
|
100% |
543
101.7 IPS |
|
|
Image Classification (I8)
|
99% |
536
100.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
234
3.90 IPS |
|
|
Image Segmentation (F16)
|
100% |
283
4.72 IPS |
|
|
Image Segmentation (I8)
|
100% |
282
4.71 IPS |
|
|
Pose Estimation (F32)
|
100% |
983
1.19 IPS |
|
|
Pose Estimation (F16)
|
100% |
1132
1.37 IPS |
|
|
Pose Estimation (I8)
|
100% |
1032
1.25 IPS |
|
|
Object Detection (F32)
|
100% |
334
24.9 IPS |
|
|
Object Detection (F16)
|
100% |
584
43.6 IPS |
|
|
Object Detection (I8)
|
97% |
342
25.5 IPS |
|
|
Face Detection (F32)
|
100% |
752
8.94 IPS |
|
|
Face Detection (F16)
|
97% |
1386
16.5 IPS |
|
|
Face Detection (I8)
|
96% |
1322
15.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
791
6.13 IPS |
|
|
Depth Estimation (F16)
|
100% |
1575
12.2 IPS |
|
|
Depth Estimation (I8)
|
99% |
1489
11.5 IPS |
|
|
Style Transfer (F32)
|
100% |
2114
2.78 IPS |
|
|
Style Transfer (F16)
|
100% |
3992
5.25 IPS |
|
|
Style Transfer (I8)
|
100% |
3893
5.12 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
669
23.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
887
31.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
884
31.6 IPS |
|
|
Text Classification (F32)
|
100% |
258
371.3 IPS |
|
|
Text Classification (F16)
|
100% |
515
740.1 IPS |
|
|
Text Classification (I8)
|
96% |
493
708.7 IPS |
|
|
Machine Translation (F32)
|
100% |
345
6.35 IPS |
|
|
Machine Translation (F16)
|
100% |
453
8.34 IPS |
|
|
Machine Translation (I8)
|
99% |
329
6.05 IPS |
