iPhone 14 Pro
Geekbench ML Score
5210
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | June 17 2024 04:39 PM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| 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% |
1277
239.0 IPS |
|
|
Image Classification (F16)
|
100% |
5831
1.09 KIPS |
|
|
Image Classification (I8)
|
99% |
5820
1.09 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1242
20.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1730
28.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
1730
28.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
10991
13.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
77178
93.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
80541
97.5 IPS |
|
|
Object Detection (F32)
|
100% |
1820
135.9 IPS |
|
|
Object Detection (F16)
|
100% |
3603
269.0 IPS |
|
|
Object Detection (I8)
|
97% |
1396
104.2 IPS |
|
|
Face Detection (F32)
|
100% |
5152
61.3 IPS |
|
|
Face Detection (F16)
|
97% |
10079
119.8 IPS |
|
|
Face Detection (I8)
|
96% |
9992
118.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
8558
66.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
35213
273.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
37165
288.2 IPS |
|
|
Style Transfer (F32)
|
100% |
19527
25.7 IPS |
|
|
Style Transfer (F16)
|
100% |
113230
148.9 IPS |
|
|
Style Transfer (I8)
|
100% |
115727
152.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4270
152.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
15395
549.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
16440
587.1 IPS |
|
|
Text Classification (F32)
|
100% |
355
510.6 IPS |
|
|
Text Classification (F16)
|
100% |
354
509.2 IPS |
|
|
Text Classification (I8)
|
96% |
409
588.3 IPS |
|
|
Machine Translation (F32)
|
100% |
598
11.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1097
20.2 IPS |
|
|
Machine Translation (I8)
|
99% |
589
10.8 IPS |
