iPhone 15 Pro Max
Geekbench ML Score
4664
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 15 2024 06:35 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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 | 7.48 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1803
337.4 IPS |
|
|
Image Classification (F16)
|
100% |
1887
353.1 IPS |
|
|
Image Classification (I8)
|
99% |
1808
338.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
1378
23.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1576
26.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
1563
26.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
14650
17.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
15603
18.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
15337
18.6 IPS |
|
|
Object Detection (F32)
|
100% |
1546
115.4 IPS |
|
|
Object Detection (F16)
|
100% |
1786
133.3 IPS |
|
|
Object Detection (I8)
|
97% |
2305
172.1 IPS |
|
|
Face Detection (F32)
|
100% |
6272
74.6 IPS |
|
|
Face Detection (F16)
|
98% |
8432
100.3 IPS |
|
|
Face Detection (I8)
|
97% |
8886
105.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
12181
94.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
13866
107.5 IPS |
|
|
Depth Estimation (I8)
|
99% |
12632
98.0 IPS |
|
|
Style Transfer (F32)
|
100% |
29379
38.6 IPS |
|
|
Style Transfer (F16)
|
100% |
35446
46.6 IPS |
|
|
Style Transfer (I8)
|
100% |
35909
47.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7104
253.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
6459
230.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
7426
265.2 IPS |
|
|
Text Classification (F32)
|
100% |
2920
4.20 KIPS |
|
|
Text Classification (F16)
|
100% |
5031
7.23 KIPS |
|
|
Text Classification (I8)
|
96% |
5008
7.20 KIPS |
|
|
Machine Translation (F32)
|
100% |
643
11.8 IPS |
|
|
Machine Translation (F16)
|
100% |
644
11.9 IPS |
|
|
Machine Translation (I8)
|
99% |
639
11.8 IPS |
