iPhone 15 Pro Max
Geekbench ML Score
6051
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 10:05 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5 |
| 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 | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1559
291.8 IPS |
|
|
Image Classification (F16)
|
100% |
6126
1.15 KIPS |
|
|
Image Classification (I8)
|
99% |
6666
1.25 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1369
22.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1709
28.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
1747
29.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
14832
18.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
83924
101.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
84554
102.4 IPS |
|
|
Object Detection (F32)
|
100% |
1501
112.0 IPS |
|
|
Object Detection (F16)
|
100% |
3752
280.1 IPS |
|
|
Object Detection (I8)
|
97% |
1791
133.7 IPS |
|
|
Face Detection (F32)
|
100% |
6367
75.7 IPS |
|
|
Face Detection (F16)
|
97% |
10573
125.7 IPS |
|
|
Face Detection (I8)
|
96% |
10535
125.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
12397
96.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
38221
296.4 IPS |
|
|
Depth Estimation (I8)
|
37% |
39709
307.9 IPS |
|
|
Style Transfer (F32)
|
100% |
29484
38.8 IPS |
|
|
Style Transfer (F16)
|
100% |
121412
159.7 IPS |
|
|
Style Transfer (I8)
|
100% |
116789
153.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6975
249.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18425
658.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
18087
645.9 IPS |
|
|
Text Classification (F32)
|
100% |
452
649.3 IPS |
|
|
Text Classification (F16)
|
100% |
495
711.8 IPS |
|
|
Text Classification (I8)
|
96% |
484
695.9 IPS |
|
|
Machine Translation (F32)
|
100% |
735
13.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1483
27.3 IPS |
|
|
Machine Translation (I8)
|
99% |
676
12.4 IPS |
