iPhone 15 Pro
Geekbench ML Score
7647
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | June 17 2024 04:35 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% |
1475
276.0 IPS |
|
|
Image Classification (F16)
|
100% |
6110
1.14 KIPS |
|
|
Image Classification (I8)
|
99% |
6630
1.24 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1453
24.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1895
31.6 IPS |
|
|
Image Segmentation (I8)
|
100% |
1867
31.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
14820
17.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
87660
106.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
89461
108.3 IPS |
|
|
Object Detection (F32)
|
100% |
1609
120.1 IPS |
|
|
Object Detection (F16)
|
100% |
3901
291.2 IPS |
|
|
Object Detection (I8)
|
97% |
2321
173.3 IPS |
|
|
Face Detection (F32)
|
100% |
6019
71.6 IPS |
|
|
Face Detection (F16)
|
97% |
12746
151.5 IPS |
|
|
Face Detection (I8)
|
96% |
12679
150.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
12310
95.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
35525
275.5 IPS |
|
|
Depth Estimation (I8)
|
37% |
36722
284.8 IPS |
|
|
Style Transfer (F32)
|
100% |
29972
39.4 IPS |
|
|
Style Transfer (F16)
|
100% |
117941
155.1 IPS |
|
|
Style Transfer (I8)
|
100% |
115401
151.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7135
254.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17840
637.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17276
617.0 IPS |
|
|
Text Classification (F32)
|
100% |
2888
4.15 KIPS |
|
|
Text Classification (F16)
|
100% |
4883
7.02 KIPS |
|
|
Text Classification (I8)
|
96% |
4899
7.04 KIPS |
|
|
Machine Translation (F32)
|
100% |
638
11.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1580
29.1 IPS |
|
|
Machine Translation (I8)
|
99% |
630
11.6 IPS |
