iPhone 13
Geekbench ML Score
6022
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | October 03 2024 06:35 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| 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 | 3.58 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
558
104.4 IPS |
|
|
Image Classification (F16)
|
100% |
6862
1.28 KIPS |
|
|
Image Classification (I8)
|
99% |
8452
1.58 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1143
19.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
2354
39.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
2347
39.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
8794
10.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
85676
103.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
88298
106.9 IPS |
|
|
Object Detection (F32)
|
100% |
1089
81.3 IPS |
|
|
Object Detection (F16)
|
100% |
4054
302.7 IPS |
|
|
Object Detection (I8)
|
97% |
1096
81.9 IPS |
|
|
Face Detection (F32)
|
100% |
3877
46.1 IPS |
|
|
Face Detection (F16)
|
97% |
16675
198.3 IPS |
|
|
Face Detection (I8)
|
96% |
16551
196.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
7601
58.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
43190
334.9 IPS |
|
|
Depth Estimation (I8)
|
37% |
40882
317.0 IPS |
|
|
Style Transfer (F32)
|
100% |
16120
21.2 IPS |
|
|
Style Transfer (F16)
|
100% |
98760
129.9 IPS |
|
|
Style Transfer (I8)
|
100% |
100251
131.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3270
116.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
26200
935.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
26055
930.5 IPS |
|
|
Text Classification (F32)
|
100% |
2209
3.17 KIPS |
|
|
Text Classification (F16)
|
100% |
2225
3.20 KIPS |
|
|
Text Classification (I8)
|
96% |
2219
3.19 KIPS |
|
|
Machine Translation (F32)
|
100% |
274
5.04 IPS |
|
|
Machine Translation (F16)
|
100% |
987
18.2 IPS |
|
|
Machine Translation (I8)
|
99% |
249
4.57 IPS |
