iPhone XR
Geekbench ML Score
659
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 19 2024 05:08 AM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.7 |
| 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
66.3 IPS |
|
|
Image Classification (F16)
|
100% |
544
101.9 IPS |
|
|
Image Classification (I8)
|
99% |
541
101.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
230
3.83 IPS |
|
|
Image Segmentation (F16)
|
100% |
273
4.56 IPS |
|
|
Image Segmentation (I8)
|
100% |
252
4.21 IPS |
|
|
Pose Estimation (F32)
|
100% |
792
0.96 IPS |
|
|
Pose Estimation (F16)
|
100% |
820
0.99 IPS |
|
|
Pose Estimation (I8)
|
100% |
886
1.07 IPS |
|
|
Object Detection (F32)
|
100% |
347
25.9 IPS |
|
|
Object Detection (F16)
|
100% |
615
45.9 IPS |
|
|
Object Detection (I8)
|
97% |
352
26.3 IPS |
|
|
Face Detection (F32)
|
100% |
700
8.33 IPS |
|
|
Face Detection (F16)
|
97% |
1397
16.6 IPS |
|
|
Face Detection (I8)
|
96% |
1386
16.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
755
5.85 IPS |
|
|
Depth Estimation (F16)
|
100% |
1615
12.5 IPS |
|
|
Depth Estimation (I8)
|
99% |
1635
12.7 IPS |
|
|
Style Transfer (F32)
|
100% |
1831
2.41 IPS |
|
|
Style Transfer (F16)
|
100% |
3583
4.71 IPS |
|
|
Style Transfer (I8)
|
100% |
3716
4.89 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
699
25.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
947
33.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
901
32.2 IPS |
|
|
Text Classification (F32)
|
100% |
243
349.3 IPS |
|
|
Text Classification (F16)
|
100% |
506
727.1 IPS |
|
|
Text Classification (I8)
|
96% |
521
748.4 IPS |
|
|
Machine Translation (F32)
|
100% |
274
5.04 IPS |
|
|
Machine Translation (F16)
|
100% |
302
5.55 IPS |
|
|
Machine Translation (I8)
|
99% |
249
4.58 IPS |
