iPhone 11
Geekbench ML Score
1211
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 06 2024 05:55 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| Model | iPhone 11 |
| Model ID | iPhone12,1 |
| Motherboard | N104AP |
| CPU Information | |
|---|---|
| Name | Apple A13 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 2.66 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 96.0 KB x 1 |
| L1 Data Cache | 48.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 3.76 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
413
77.3 IPS |
|
|
Image Classification (F16)
|
100% |
744
139.2 IPS |
|
|
Image Classification (I8)
|
99% |
740
138.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
278
4.65 IPS |
|
|
Image Segmentation (F16)
|
100% |
376
6.29 IPS |
|
|
Image Segmentation (I8)
|
100% |
371
6.20 IPS |
|
|
Pose Estimation (F32)
|
100% |
1768
2.14 IPS |
|
|
Pose Estimation (F16)
|
100% |
4022
4.87 IPS |
|
|
Pose Estimation (I8)
|
100% |
4063
4.92 IPS |
|
|
Object Detection (F32)
|
100% |
426
31.8 IPS |
|
|
Object Detection (F16)
|
100% |
838
62.6 IPS |
|
|
Object Detection (I8)
|
97% |
428
31.9 IPS |
|
|
Face Detection (F32)
|
100% |
909
10.8 IPS |
|
|
Face Detection (F16)
|
97% |
1728
20.5 IPS |
|
|
Face Detection (I8)
|
97% |
1749
20.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
1643
12.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
3853
29.9 IPS |
|
|
Depth Estimation (I8)
|
99% |
3809
29.5 IPS |
|
|
Style Transfer (F32)
|
100% |
3966
5.22 IPS |
|
|
Style Transfer (F16)
|
100% |
7811
10.3 IPS |
|
|
Style Transfer (I8)
|
100% |
7799
10.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1195
42.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1828
65.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1842
65.8 IPS |
|
|
Text Classification (F32)
|
100% |
844
1.21 KIPS |
|
|
Text Classification (F16)
|
100% |
1400
2.01 KIPS |
|
|
Text Classification (I8)
|
96% |
1405
2.02 KIPS |
|
|
Machine Translation (F32)
|
100% |
374
6.89 IPS |
|
|
Machine Translation (F16)
|
100% |
543
9.99 IPS |
|
|
Machine Translation (I8)
|
99% |
373
6.86 IPS |
