iPhone 15 Pro Max
Geekbench ML Score
3696
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 16 2024 08:58 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| 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% |
1766
330.4 IPS |
|
|
Image Classification (F16)
|
100% |
1726
322.9 IPS |
|
|
Image Classification (I8)
|
99% |
1734
324.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
1393
23.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1551
25.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
1565
26.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
14900
18.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
15864
19.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
15485
18.8 IPS |
|
|
Object Detection (F32)
|
100% |
1506
112.4 IPS |
|
|
Object Detection (F16)
|
100% |
1549
115.7 IPS |
|
|
Object Detection (I8)
|
97% |
1585
118.3 IPS |
|
|
Face Detection (F32)
|
100% |
6305
75.0 IPS |
|
|
Face Detection (F16)
|
98% |
8312
98.8 IPS |
|
|
Face Detection (I8)
|
97% |
8553
101.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
12452
96.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
14050
109.0 IPS |
|
|
Depth Estimation (I8)
|
37% |
12890
100.0 IPS |
|
|
Style Transfer (F32)
|
100% |
29741
39.1 IPS |
|
|
Style Transfer (F16)
|
100% |
36579
48.1 IPS |
|
|
Style Transfer (I8)
|
100% |
36311
47.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7103
253.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
7804
278.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
6654
237.6 IPS |
|
|
Text Classification (F32)
|
100% |
487
699.7 IPS |
|
|
Text Classification (F16)
|
100% |
497
713.7 IPS |
|
|
Text Classification (I8)
|
96% |
312
448.1 IPS |
|
|
Machine Translation (F32)
|
100% |
733
13.5 IPS |
|
|
Machine Translation (F16)
|
100% |
811
14.9 IPS |
|
|
Machine Translation (I8)
|
99% |
678
12.5 IPS |
