iPhone 15 Pro
Geekbench ML Score
6041
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 07 2024 08:16 AM |
| Views | 4 |
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% |
1699
318.0 IPS |
|
|
Image Classification (F16)
|
100% |
6232
1.17 KIPS |
|
|
Image Classification (I8)
|
99% |
6897
1.29 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1443
24.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
1825
30.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
1847
30.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
14659
17.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
83158
100.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
83859
101.6 IPS |
|
|
Object Detection (F32)
|
100% |
1634
122.0 IPS |
|
|
Object Detection (F16)
|
100% |
3996
298.3 IPS |
|
|
Object Detection (I8)
|
97% |
1472
109.9 IPS |
|
|
Face Detection (F32)
|
100% |
6557
78.0 IPS |
|
|
Face Detection (F16)
|
97% |
10684
127.0 IPS |
|
|
Face Detection (I8)
|
96% |
10676
126.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
12313
95.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
37645
291.9 IPS |
|
|
Depth Estimation (I8)
|
37% |
45408
352.1 IPS |
|
|
Style Transfer (F32)
|
100% |
28440
37.4 IPS |
|
|
Style Transfer (F16)
|
100% |
121379
159.7 IPS |
|
|
Style Transfer (I8)
|
100% |
125548
165.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6778
242.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18747
669.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
17620
629.3 IPS |
|
|
Text Classification (F32)
|
100% |
447
642.0 IPS |
|
|
Text Classification (F16)
|
100% |
479
688.7 IPS |
|
|
Text Classification (I8)
|
96% |
298
428.9 IPS |
|
|
Machine Translation (F32)
|
100% |
758
13.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1545
28.4 IPS |
|
|
Machine Translation (I8)
|
99% |
681
12.5 IPS |
