iPhone 14 Pro
Geekbench ML Score
5091
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 19 2024 09:25 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| Model | iPhone 14 Pro |
| Model ID | iPhone15,2 |
| Motherboard | D73AP |
| CPU Information | |
|---|---|
| Name | Apple A16 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.46 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 | 5.50 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1114
208.4 IPS |
|
|
Image Classification (F16)
|
100% |
5346
1.00 KIPS |
|
|
Image Classification (I8)
|
99% |
5855
1.10 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1233
20.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1690
28.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
1742
29.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
11098
13.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
77796
94.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
81706
98.9 IPS |
|
|
Object Detection (F32)
|
100% |
1365
101.9 IPS |
|
|
Object Detection (F16)
|
100% |
3642
271.9 IPS |
|
|
Object Detection (I8)
|
97% |
1437
107.2 IPS |
|
|
Face Detection (F32)
|
100% |
5191
61.7 IPS |
|
|
Face Detection (F16)
|
97% |
10367
123.3 IPS |
|
|
Face Detection (I8)
|
96% |
10195
121.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
8621
66.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
34665
268.8 IPS |
|
|
Depth Estimation (I8)
|
37% |
37493
290.8 IPS |
|
|
Style Transfer (F32)
|
100% |
20169
26.5 IPS |
|
|
Style Transfer (F16)
|
100% |
115520
152.0 IPS |
|
|
Style Transfer (I8)
|
100% |
116538
153.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4381
156.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
16727
597.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17307
618.1 IPS |
|
|
Text Classification (F32)
|
100% |
362
520.7 IPS |
|
|
Text Classification (F16)
|
100% |
356
511.6 IPS |
|
|
Text Classification (I8)
|
96% |
243
349.0 IPS |
|
|
Machine Translation (F32)
|
100% |
603
11.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1069
19.7 IPS |
|
|
Machine Translation (I8)
|
99% |
588
10.8 IPS |
