iPhone 15 Pro
Geekbench ML Score
5955
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 26 2024 05:35 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% |
1638
306.4 IPS |
|
|
Image Classification (F16)
|
100% |
6160
1.15 KIPS |
|
|
Image Classification (I8)
|
99% |
6747
1.26 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1458
24.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1863
31.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
1838
30.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
14590
17.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
82574
100.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
85604
103.7 IPS |
|
|
Object Detection (F32)
|
100% |
1453
108.5 IPS |
|
|
Object Detection (F16)
|
100% |
3904
291.4 IPS |
|
|
Object Detection (I8)
|
97% |
1675
125.1 IPS |
|
|
Face Detection (F32)
|
100% |
6525
77.6 IPS |
|
|
Face Detection (F16)
|
97% |
10565
125.6 IPS |
|
|
Face Detection (I8)
|
96% |
10525
125.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
12158
94.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
38091
295.4 IPS |
|
|
Depth Estimation (I8)
|
37% |
38757
300.6 IPS |
|
|
Style Transfer (F32)
|
100% |
27693
36.4 IPS |
|
|
Style Transfer (F16)
|
100% |
123245
162.1 IPS |
|
|
Style Transfer (I8)
|
100% |
120946
159.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6866
245.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18247
651.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
16661
595.0 IPS |
|
|
Text Classification (F32)
|
100% |
436
627.3 IPS |
|
|
Text Classification (F16)
|
100% |
470
675.4 IPS |
|
|
Text Classification (I8)
|
96% |
301
432.4 IPS |
|
|
Machine Translation (F32)
|
100% |
743
13.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1525
28.1 IPS |
|
|
Machine Translation (I8)
|
99% |
678
12.5 IPS |
