iPhone 15 Pro
Geekbench ML Score
7642
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | June 17 2024 04:43 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| Model | iPhone 15 Pro |
| Model ID | iPhone16,1 |
| Motherboard | D83AP |
| CPU Information | |
|---|---|
| Name | Apple A17 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.78 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 | 7.51 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1126
210.8 IPS |
|
|
Image Classification (F16)
|
100% |
6188
1.16 KIPS |
|
|
Image Classification (I8)
|
99% |
6795
1.27 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1407
23.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1824
30.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
1850
30.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
14791
17.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
87407
105.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
87359
105.8 IPS |
|
|
Object Detection (F32)
|
100% |
1536
114.7 IPS |
|
|
Object Detection (F16)
|
100% |
4481
334.5 IPS |
|
|
Object Detection (I8)
|
97% |
2308
172.3 IPS |
|
|
Face Detection (F32)
|
100% |
5499
65.4 IPS |
|
|
Face Detection (F16)
|
97% |
12512
148.8 IPS |
|
|
Face Detection (I8)
|
96% |
12879
153.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
12267
95.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
37505
290.9 IPS |
|
|
Depth Estimation (I8)
|
37% |
46324
359.2 IPS |
|
|
Style Transfer (F32)
|
100% |
29732
39.1 IPS |
|
|
Style Transfer (F16)
|
100% |
112171
147.6 IPS |
|
|
Style Transfer (I8)
|
100% |
116043
152.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7206
257.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17643
630.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17702
632.2 IPS |
|
|
Text Classification (F32)
|
100% |
3003
4.32 KIPS |
|
|
Text Classification (F16)
|
100% |
5211
7.49 KIPS |
|
|
Text Classification (I8)
|
96% |
5247
7.54 KIPS |
|
|
Machine Translation (F32)
|
100% |
606
11.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1637
30.1 IPS |
|
|
Machine Translation (I8)
|
99% |
581
10.7 IPS |
