iPhone 15 Pro Max
Geekbench ML Score
3626
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 09 2024 06:24 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% |
1607
300.8 IPS |
|
|
Image Classification (F16)
|
100% |
1457
272.6 IPS |
|
|
Image Classification (I8)
|
99% |
1653
309.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
1393
23.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1542
25.8 IPS |
|
|
Image Segmentation (I8)
|
100% |
1553
25.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
14800
17.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
15815
19.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
15552
18.8 IPS |
|
|
Object Detection (F32)
|
100% |
2054
153.4 IPS |
|
|
Object Detection (F16)
|
100% |
1459
108.9 IPS |
|
|
Object Detection (I8)
|
97% |
1568
117.1 IPS |
|
|
Face Detection (F32)
|
100% |
6226
74.0 IPS |
|
|
Face Detection (F16)
|
98% |
8198
97.5 IPS |
|
|
Face Detection (I8)
|
97% |
8573
101.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
12368
95.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
13893
107.7 IPS |
|
|
Depth Estimation (I8)
|
37% |
12677
98.3 IPS |
|
|
Style Transfer (F32)
|
100% |
29408
38.7 IPS |
|
|
Style Transfer (F16)
|
100% |
31850
41.9 IPS |
|
|
Style Transfer (I8)
|
100% |
34543
45.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6922
247.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
6726
240.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
6740
240.7 IPS |
|
|
Text Classification (F32)
|
100% |
466
669.6 IPS |
|
|
Text Classification (F16)
|
100% |
494
709.8 IPS |
|
|
Text Classification (I8)
|
96% |
310
444.9 IPS |
|
|
Machine Translation (F32)
|
100% |
748
13.8 IPS |
|
|
Machine Translation (F16)
|
100% |
788
14.5 IPS |
|
|
Machine Translation (I8)
|
99% |
678
12.5 IPS |
