iPhone 15 Pro Max
Geekbench ML Score
3636
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 07 2024 09:12 AM |
| Views | 1 |
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% |
1612
301.7 IPS |
|
|
Image Classification (F16)
|
100% |
1687
315.6 IPS |
|
|
Image Classification (I8)
|
99% |
1622
303.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
1361
22.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1535
25.6 IPS |
|
|
Image Segmentation (I8)
|
100% |
1525
25.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
14778
17.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
15868
19.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
15524
18.8 IPS |
|
|
Object Detection (F32)
|
100% |
1463
109.2 IPS |
|
|
Object Detection (F16)
|
100% |
1530
114.2 IPS |
|
|
Object Detection (I8)
|
97% |
1798
134.3 IPS |
|
|
Face Detection (F32)
|
100% |
6221
74.0 IPS |
|
|
Face Detection (F16)
|
98% |
8423
100.2 IPS |
|
|
Face Detection (I8)
|
97% |
8572
101.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
12411
96.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
13821
107.2 IPS |
|
|
Depth Estimation (I8)
|
37% |
12718
98.6 IPS |
|
|
Style Transfer (F32)
|
100% |
29700
39.1 IPS |
|
|
Style Transfer (F16)
|
100% |
31608
41.6 IPS |
|
|
Style Transfer (I8)
|
100% |
34738
45.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7022
250.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
7505
268.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
6884
245.9 IPS |
|
|
Text Classification (F32)
|
100% |
478
686.9 IPS |
|
|
Text Classification (F16)
|
100% |
487
699.4 IPS |
|
|
Text Classification (I8)
|
96% |
304
436.2 IPS |
|
|
Machine Translation (F32)
|
100% |
739
13.6 IPS |
|
|
Machine Translation (F16)
|
100% |
788
14.5 IPS |
|
|
Machine Translation (I8)
|
99% |
671
12.3 IPS |
