iPhone 15 Pro Max
Geekbench ML Score
3611
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 15 2024 05:09 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| 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% |
1506
281.8 IPS |
|
|
Image Classification (F16)
|
100% |
1361
254.8 IPS |
|
|
Image Classification (I8)
|
99% |
1679
314.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
1414
23.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1538
25.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
1539
25.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
14831
18.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
15812
19.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
15504
18.8 IPS |
|
|
Object Detection (F32)
|
100% |
1653
123.4 IPS |
|
|
Object Detection (F16)
|
100% |
1565
116.9 IPS |
|
|
Object Detection (I8)
|
97% |
1625
121.3 IPS |
|
|
Face Detection (F32)
|
100% |
6103
72.6 IPS |
|
|
Face Detection (F16)
|
98% |
8112
96.4 IPS |
|
|
Face Detection (I8)
|
97% |
8459
100.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
12301
95.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
13698
106.2 IPS |
|
|
Depth Estimation (I8)
|
37% |
12666
98.2 IPS |
|
|
Style Transfer (F32)
|
100% |
29674
39.0 IPS |
|
|
Style Transfer (F16)
|
100% |
31897
42.0 IPS |
|
|
Style Transfer (I8)
|
100% |
34855
45.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6769
241.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
7367
263.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
7466
266.6 IPS |
|
|
Text Classification (F32)
|
100% |
474
681.0 IPS |
|
|
Text Classification (F16)
|
100% |
492
707.0 IPS |
|
|
Text Classification (I8)
|
96% |
301
433.1 IPS |
|
|
Machine Translation (F32)
|
100% |
744
13.7 IPS |
|
|
Machine Translation (F16)
|
100% |
785
14.4 IPS |
|
|
Machine Translation (I8)
|
99% |
680
12.5 IPS |
