iPhone 15 Pro
Geekbench ML Score
6199
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | July 27 2024 06:32 AM |
| Views | 3 |
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% |
1520
284.4 IPS |
|
|
Image Classification (F16)
|
100% |
6233
1.17 KIPS |
|
|
Image Classification (I8)
|
99% |
6826
1.28 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1474
24.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1895
31.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
1862
31.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
14866
18.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
83168
100.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
87573
106.0 IPS |
|
|
Object Detection (F32)
|
100% |
1786
133.3 IPS |
|
|
Object Detection (F16)
|
100% |
3825
285.6 IPS |
|
|
Object Detection (I8)
|
97% |
2327
173.7 IPS |
|
|
Face Detection (F32)
|
100% |
6137
73.0 IPS |
|
|
Face Detection (F16)
|
97% |
10672
126.9 IPS |
|
|
Face Detection (I8)
|
96% |
10860
129.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
12389
96.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
38730
300.4 IPS |
|
|
Depth Estimation (I8)
|
37% |
50411
390.9 IPS |
|
|
Style Transfer (F32)
|
100% |
28869
38.0 IPS |
|
|
Style Transfer (F16)
|
100% |
123754
162.8 IPS |
|
|
Style Transfer (I8)
|
100% |
121581
159.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7305
260.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17999
642.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
19202
685.8 IPS |
|
|
Text Classification (F32)
|
100% |
457
656.6 IPS |
|
|
Text Classification (F16)
|
100% |
486
698.5 IPS |
|
|
Text Classification (I8)
|
96% |
301
431.9 IPS |
|
|
Machine Translation (F32)
|
100% |
752
13.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1557
28.7 IPS |
|
|
Machine Translation (I8)
|
99% |
689
12.7 IPS |
