iPhone 13 Pro
Geekbench ML Score
5047
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | January 09 2024 12:05 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.2.1 |
| Model | iPhone 13 Pro |
| Model ID | iPhone14,2 |
| Motherboard | D63AP |
| 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 | 5.51 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1139
213.2 IPS |
|
|
Image Classification (F16)
|
100% |
5302
992.2 IPS |
|
|
Image Classification (I8)
|
99% |
4765
891.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
1191
19.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1566
26.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
1579
26.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
10754
13.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
74793
90.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
57707
69.9 IPS |
|
|
Object Detection (F32)
|
100% |
1369
102.2 IPS |
|
|
Object Detection (F16)
|
100% |
3660
273.2 IPS |
|
|
Object Detection (I8)
|
97% |
1391
103.8 IPS |
|
|
Face Detection (F32)
|
100% |
4336
51.6 IPS |
|
|
Face Detection (F16)
|
97% |
9485
112.8 IPS |
|
|
Face Detection (I8)
|
96% |
9915
117.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
8593
66.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
33321
258.4 IPS |
|
|
Depth Estimation (I8)
|
37% |
37775
292.9 IPS |
|
|
Style Transfer (F32)
|
100% |
18734
24.6 IPS |
|
|
Style Transfer (F16)
|
100% |
101073
133.0 IPS |
|
|
Style Transfer (I8)
|
100% |
93813
123.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4866
173.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
13705
489.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
15621
557.9 IPS |
|
|
Text Classification (F32)
|
100% |
387
556.4 IPS |
|
|
Text Classification (F16)
|
100% |
969
1.39 KIPS |
|
|
Text Classification (I8)
|
96% |
399
572.7 IPS |
|
|
Machine Translation (F32)
|
100% |
587
10.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1165
21.4 IPS |
|
|
Machine Translation (I8)
|
99% |
540
9.94 IPS |
