iPhone 15 Pro Max
Geekbench ML Score
3641
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 09 2024 03:11 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| Model | iPhone 15 Pro Max |
| Model ID | iPhone16,2 |
| Motherboard | D84AP |
| 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 | 7.44 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1611
301.4 IPS |
|
|
Image Classification (F16)
|
100% |
1965
367.8 IPS |
|
|
Image Classification (I8)
|
99% |
1835
343.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
1365
22.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1539
25.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
1565
26.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
14837
18.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
15773
19.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
15393
18.6 IPS |
|
|
Object Detection (F32)
|
100% |
1612
120.4 IPS |
|
|
Object Detection (F16)
|
100% |
1540
114.9 IPS |
|
|
Object Detection (I8)
|
97% |
1598
119.3 IPS |
|
|
Face Detection (F32)
|
100% |
5996
71.3 IPS |
|
|
Face Detection (F16)
|
98% |
7914
94.1 IPS |
|
|
Face Detection (I8)
|
97% |
8525
101.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
12437
96.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
13877
107.6 IPS |
|
|
Depth Estimation (I8)
|
37% |
12744
98.8 IPS |
|
|
Style Transfer (F32)
|
100% |
29671
39.0 IPS |
|
|
Style Transfer (F16)
|
100% |
32169
42.3 IPS |
|
|
Style Transfer (I8)
|
100% |
32082
42.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6923
247.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
7527
268.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
6811
243.2 IPS |
|
|
Text Classification (F32)
|
100% |
458
658.3 IPS |
|
|
Text Classification (F16)
|
100% |
488
701.9 IPS |
|
|
Text Classification (I8)
|
96% |
301
432.1 IPS |
|
|
Machine Translation (F32)
|
100% |
744
13.7 IPS |
|
|
Machine Translation (F16)
|
100% |
781
14.4 IPS |
|
|
Machine Translation (I8)
|
99% |
670
12.3 IPS |
