iPhone XR
Geekbench ML Score
683
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 27 2024 05:20 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% |
347
64.9 IPS |
|
|
Image Classification (F16)
|
100% |
532
99.5 IPS |
|
|
Image Classification (I8)
|
99% |
529
99.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
230
3.85 IPS |
|
|
Image Segmentation (F16)
|
100% |
276
4.60 IPS |
|
|
Image Segmentation (I8)
|
100% |
275
4.60 IPS |
|
|
Pose Estimation (F32)
|
100% |
897
1.09 IPS |
|
|
Pose Estimation (F16)
|
100% |
1115
1.35 IPS |
|
|
Pose Estimation (I8)
|
100% |
1121
1.36 IPS |
|
|
Object Detection (F32)
|
100% |
329
24.5 IPS |
|
|
Object Detection (F16)
|
100% |
583
43.6 IPS |
|
|
Object Detection (I8)
|
97% |
334
25.0 IPS |
|
|
Face Detection (F32)
|
100% |
736
8.75 IPS |
|
|
Face Detection (F16)
|
97% |
1210
14.4 IPS |
|
|
Face Detection (I8)
|
96% |
1331
15.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
759
5.89 IPS |
|
|
Depth Estimation (F16)
|
100% |
1443
11.2 IPS |
|
|
Depth Estimation (I8)
|
99% |
1442
11.2 IPS |
|
|
Style Transfer (F32)
|
100% |
1919
2.52 IPS |
|
|
Style Transfer (F16)
|
100% |
3954
5.20 IPS |
|
|
Style Transfer (I8)
|
100% |
3962
5.21 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
653
23.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
878
31.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
902
32.2 IPS |
|
|
Text Classification (F32)
|
100% |
257
369.7 IPS |
|
|
Text Classification (F16)
|
100% |
513
737.4 IPS |
|
|
Text Classification (I8)
|
96% |
513
737.7 IPS |
|
|
Machine Translation (F32)
|
100% |
325
5.98 IPS |
|
|
Machine Translation (F16)
|
100% |
446
8.22 IPS |
|
|
Machine Translation (I8)
|
99% |
322
5.93 IPS |
