iPhone XR
Geekbench ML Score
640
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | April 26 2024 09:09 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% |
321
60.1 IPS |
|
|
Image Classification (F16)
|
100% |
491
91.8 IPS |
|
|
Image Classification (I8)
|
99% |
505
94.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
214
3.58 IPS |
|
|
Image Segmentation (F16)
|
100% |
264
4.40 IPS |
|
|
Image Segmentation (I8)
|
100% |
261
4.36 IPS |
|
|
Pose Estimation (F32)
|
100% |
759
0.92 IPS |
|
|
Pose Estimation (F16)
|
100% |
742
0.90 IPS |
|
|
Pose Estimation (I8)
|
100% |
849
1.03 IPS |
|
|
Object Detection (F32)
|
100% |
333
24.9 IPS |
|
|
Object Detection (F16)
|
100% |
607
45.3 IPS |
|
|
Object Detection (I8)
|
97% |
341
25.4 IPS |
|
|
Face Detection (F32)
|
100% |
597
7.09 IPS |
|
|
Face Detection (F16)
|
97% |
1364
16.2 IPS |
|
|
Face Detection (I8)
|
96% |
1271
15.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
738
5.72 IPS |
|
|
Depth Estimation (F16)
|
100% |
1506
11.7 IPS |
|
|
Depth Estimation (I8)
|
99% |
1615
12.5 IPS |
|
|
Style Transfer (F32)
|
100% |
2013
2.65 IPS |
|
|
Style Transfer (F16)
|
100% |
4147
5.46 IPS |
|
|
Style Transfer (I8)
|
100% |
3948
5.19 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
686
24.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
936
33.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
936
33.4 IPS |
|
|
Text Classification (F32)
|
100% |
258
370.9 IPS |
|
|
Text Classification (F16)
|
100% |
504
724.2 IPS |
|
|
Text Classification (I8)
|
96% |
511
735.1 IPS |
|
|
Machine Translation (F32)
|
100% |
255
4.70 IPS |
|
|
Machine Translation (F16)
|
100% |
322
5.93 IPS |
|
|
Machine Translation (I8)
|
99% |
203
3.73 IPS |
