iPhone 15 Pro
Geekbench ML Score
6088
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 04:05 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| 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% |
1510
282.5 IPS |
|
|
Image Classification (F16)
|
100% |
6272
1.17 KIPS |
|
|
Image Classification (I8)
|
99% |
6854
1.28 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1500
25.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1884
31.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
1924
32.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
14870
18.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
82415
99.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
86540
104.8 IPS |
|
|
Object Detection (F32)
|
100% |
1456
108.7 IPS |
|
|
Object Detection (F16)
|
100% |
3795
283.3 IPS |
|
|
Object Detection (I8)
|
97% |
1593
118.9 IPS |
|
|
Face Detection (F32)
|
100% |
6190
73.6 IPS |
|
|
Face Detection (F16)
|
97% |
10586
125.9 IPS |
|
|
Face Detection (I8)
|
96% |
10627
126.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
12575
97.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
38202
296.3 IPS |
|
|
Depth Estimation (I8)
|
37% |
50439
391.2 IPS |
|
|
Style Transfer (F32)
|
100% |
29118
38.3 IPS |
|
|
Style Transfer (F16)
|
100% |
122085
160.6 IPS |
|
|
Style Transfer (I8)
|
100% |
120959
159.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7258
259.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18373
656.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
18290
653.2 IPS |
|
|
Text Classification (F32)
|
100% |
459
659.2 IPS |
|
|
Text Classification (F16)
|
100% |
497
713.8 IPS |
|
|
Text Classification (I8)
|
96% |
338
485.4 IPS |
|
|
Machine Translation (F32)
|
100% |
726
13.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1555
28.6 IPS |
|
|
Machine Translation (I8)
|
99% |
677
12.5 IPS |
