iPhone XR
Geekbench ML Score
643
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 24 2024 07:41 PM |
| 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% |
220
41.2 IPS |
|
|
Image Classification (F16)
|
100% |
394
73.7 IPS |
|
|
Image Classification (I8)
|
99% |
398
74.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
190
3.17 IPS |
|
|
Image Segmentation (F16)
|
100% |
269
4.50 IPS |
|
|
Image Segmentation (I8)
|
100% |
279
4.65 IPS |
|
|
Pose Estimation (F32)
|
100% |
852
1.03 IPS |
|
|
Pose Estimation (F16)
|
100% |
901
1.09 IPS |
|
|
Pose Estimation (I8)
|
100% |
950
1.15 IPS |
|
|
Object Detection (F32)
|
100% |
332
24.8 IPS |
|
|
Object Detection (F16)
|
100% |
592
44.2 IPS |
|
|
Object Detection (I8)
|
97% |
325
24.3 IPS |
|
|
Face Detection (F32)
|
100% |
697
8.28 IPS |
|
|
Face Detection (F16)
|
97% |
1272
15.1 IPS |
|
|
Face Detection (I8)
|
96% |
1292
15.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
778
6.03 IPS |
|
|
Depth Estimation (F16)
|
100% |
1386
10.8 IPS |
|
|
Depth Estimation (I8)
|
99% |
1525
11.8 IPS |
|
|
Style Transfer (F32)
|
100% |
1937
2.55 IPS |
|
|
Style Transfer (F16)
|
100% |
3644
4.79 IPS |
|
|
Style Transfer (I8)
|
100% |
3883
5.11 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
657
23.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
904
32.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
893
31.9 IPS |
|
|
Text Classification (F32)
|
100% |
249
357.6 IPS |
|
|
Text Classification (F16)
|
100% |
511
734.0 IPS |
|
|
Text Classification (I8)
|
96% |
515
739.8 IPS |
|
|
Machine Translation (F32)
|
100% |
330
6.07 IPS |
|
|
Machine Translation (F16)
|
100% |
429
7.89 IPS |
|
|
Machine Translation (I8)
|
99% |
310
5.70 IPS |
