iPhone 15 Pro
Geekbench ML Score
6032
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | June 17 2024 04:29 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| 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 | 7.47 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1660
310.6 IPS |
|
|
Image Classification (F16)
|
100% |
6190
1.16 KIPS |
|
|
Image Classification (I8)
|
99% |
6954
1.30 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1259
21.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1616
27.0 IPS |
|
|
Image Segmentation (I8)
|
100% |
1632
27.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
14716
17.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
84556
102.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
85772
103.9 IPS |
|
|
Object Detection (F32)
|
100% |
2410
179.9 IPS |
|
|
Object Detection (F16)
|
100% |
3553
265.2 IPS |
|
|
Object Detection (I8)
|
97% |
1611
120.3 IPS |
|
|
Face Detection (F32)
|
100% |
5741
68.3 IPS |
|
|
Face Detection (F16)
|
97% |
10581
125.8 IPS |
|
|
Face Detection (I8)
|
96% |
10971
130.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
12505
97.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
38676
299.9 IPS |
|
|
Depth Estimation (I8)
|
37% |
38432
298.0 IPS |
|
|
Style Transfer (F32)
|
100% |
29499
38.8 IPS |
|
|
Style Transfer (F16)
|
100% |
117028
153.9 IPS |
|
|
Style Transfer (I8)
|
100% |
120863
159.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7264
259.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18252
651.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
18524
661.6 IPS |
|
|
Text Classification (F32)
|
100% |
485
696.7 IPS |
|
|
Text Classification (F16)
|
100% |
494
709.4 IPS |
|
|
Text Classification (I8)
|
96% |
311
447.4 IPS |
|
|
Machine Translation (F32)
|
100% |
745
13.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1523
28.0 IPS |
|
|
Machine Translation (I8)
|
99% |
692
12.7 IPS |
