iPhone 13
Geekbench ML Score
4382
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | April 27 2024 04:08 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| Model | iPhone 13 |
| Model ID | iPhone14,5 |
| Motherboard | D17AP |
| CPU Information | |
|---|---|
| Name | Apple A15 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.23 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 3.54 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
793
148.3 IPS |
|
|
Image Classification (F16)
|
100% |
5168
967.0 IPS |
|
|
Image Classification (I8)
|
99% |
4685
876.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
1189
19.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1721
28.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
1683
28.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
8812
10.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
71164
86.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
58259
70.5 IPS |
|
|
Object Detection (F32)
|
100% |
863
64.4 IPS |
|
|
Object Detection (F16)
|
100% |
3910
291.9 IPS |
|
|
Object Detection (I8)
|
97% |
823
61.4 IPS |
|
|
Face Detection (F32)
|
100% |
2075
24.7 IPS |
|
|
Face Detection (F16)
|
97% |
9867
117.3 IPS |
|
|
Face Detection (I8)
|
96% |
10025
119.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
5774
44.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
32171
249.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
31982
248.0 IPS |
|
|
Style Transfer (F32)
|
100% |
16751
22.0 IPS |
|
|
Style Transfer (F16)
|
100% |
108111
142.2 IPS |
|
|
Style Transfer (I8)
|
100% |
99367
130.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3209
114.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
10930
390.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
14417
514.9 IPS |
|
|
Text Classification (F32)
|
100% |
494
710.4 IPS |
|
|
Text Classification (F16)
|
100% |
1051
1.51 KIPS |
|
|
Text Classification (I8)
|
96% |
342
491.7 IPS |
|
|
Machine Translation (F32)
|
100% |
455
8.37 IPS |
|
|
Machine Translation (F16)
|
100% |
656
12.1 IPS |
|
|
Machine Translation (I8)
|
99% |
452
8.32 IPS |
