iPhone 15 Pro Max
Geekbench ML Score
3642
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 09 2024 09:52 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% |
1269
237.4 IPS |
|
|
Image Classification (F16)
|
100% |
1519
284.3 IPS |
|
|
Image Classification (I8)
|
99% |
1908
357.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
1377
23.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1530
25.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
1528
25.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
14867
18.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
15779
19.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
15587
18.9 IPS |
|
|
Object Detection (F32)
|
100% |
1496
111.7 IPS |
|
|
Object Detection (F16)
|
100% |
1569
117.1 IPS |
|
|
Object Detection (I8)
|
97% |
2273
169.7 IPS |
|
|
Face Detection (F32)
|
100% |
6253
74.3 IPS |
|
|
Face Detection (F16)
|
98% |
8168
97.1 IPS |
|
|
Face Detection (I8)
|
97% |
8501
101.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
12252
95.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
13831
107.3 IPS |
|
|
Depth Estimation (I8)
|
37% |
12667
98.2 IPS |
|
|
Style Transfer (F32)
|
100% |
29247
38.5 IPS |
|
|
Style Transfer (F16)
|
100% |
36380
47.9 IPS |
|
|
Style Transfer (I8)
|
100% |
34841
45.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7005
250.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
7351
262.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
6341
226.4 IPS |
|
|
Text Classification (F32)
|
100% |
449
645.8 IPS |
|
|
Text Classification (F16)
|
100% |
487
699.5 IPS |
|
|
Text Classification (I8)
|
96% |
302
434.2 IPS |
|
|
Machine Translation (F32)
|
100% |
746
13.7 IPS |
|
|
Machine Translation (F16)
|
100% |
795
14.6 IPS |
|
|
Machine Translation (I8)
|
99% |
679
12.5 IPS |
