iPhone 15 Pro
Geekbench ML Score
6239
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | April 25 2024 05:22 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% |
1657
310.1 IPS |
|
|
Image Classification (F16)
|
100% |
6272
1.17 KIPS |
|
|
Image Classification (I8)
|
99% |
7028
1.32 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1489
24.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1910
31.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
1892
31.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
14819
17.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
83062
100.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
87915
106.5 IPS |
|
|
Object Detection (F32)
|
100% |
1678
125.3 IPS |
|
|
Object Detection (F16)
|
100% |
3956
295.3 IPS |
|
|
Object Detection (I8)
|
97% |
2362
176.3 IPS |
|
|
Face Detection (F32)
|
100% |
6404
76.1 IPS |
|
|
Face Detection (F16)
|
97% |
10618
126.2 IPS |
|
|
Face Detection (I8)
|
96% |
10737
127.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
12534
97.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
40883
317.0 IPS |
|
|
Depth Estimation (I8)
|
37% |
49896
386.9 IPS |
|
|
Style Transfer (F32)
|
100% |
29706
39.1 IPS |
|
|
Style Transfer (F16)
|
100% |
118956
156.5 IPS |
|
|
Style Transfer (I8)
|
100% |
122501
161.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7225
258.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
16669
595.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
18815
671.9 IPS |
|
|
Text Classification (F32)
|
100% |
480
690.1 IPS |
|
|
Text Classification (F16)
|
100% |
490
704.6 IPS |
|
|
Text Classification (I8)
|
96% |
305
438.8 IPS |
|
|
Machine Translation (F32)
|
100% |
765
14.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1552
28.6 IPS |
|
|
Machine Translation (I8)
|
99% |
688
12.7 IPS |
