iPhone 15 Pro Max
Geekbench ML Score
5968
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 07:24 AM |
| Views | 2 |
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% |
1236
231.3 IPS |
|
|
Image Classification (F16)
|
100% |
6339
1.19 KIPS |
|
|
Image Classification (I8)
|
99% |
6890
1.29 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1386
23.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
1757
29.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
1763
29.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
14830
18.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
83488
101.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
84205
102.0 IPS |
|
|
Object Detection (F32)
|
100% |
1496
111.7 IPS |
|
|
Object Detection (F16)
|
100% |
3822
285.3 IPS |
|
|
Object Detection (I8)
|
97% |
1643
122.6 IPS |
|
|
Face Detection (F32)
|
100% |
6143
73.0 IPS |
|
|
Face Detection (F16)
|
97% |
10451
124.3 IPS |
|
|
Face Detection (I8)
|
96% |
10677
126.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
12368
95.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
37245
288.8 IPS |
|
|
Depth Estimation (I8)
|
37% |
48844
378.8 IPS |
|
|
Style Transfer (F32)
|
100% |
29811
39.2 IPS |
|
|
Style Transfer (F16)
|
100% |
117272
154.3 IPS |
|
|
Style Transfer (I8)
|
100% |
120763
158.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6461
230.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17948
641.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
18711
668.2 IPS |
|
|
Text Classification (F32)
|
100% |
479
687.8 IPS |
|
|
Text Classification (F16)
|
100% |
509
732.0 IPS |
|
|
Text Classification (I8)
|
96% |
328
471.4 IPS |
|
|
Machine Translation (F32)
|
100% |
738
13.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1548
28.5 IPS |
|
|
Machine Translation (I8)
|
99% |
644
11.9 IPS |
