iPhone 15 Pro Max
Geekbench ML Score
5922
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 04:09 PM |
| 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% |
1659
310.4 IPS |
|
|
Image Classification (F16)
|
100% |
6239
1.17 KIPS |
|
|
Image Classification (I8)
|
99% |
6780
1.27 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1307
21.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1702
28.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
1769
29.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
14557
17.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
82449
99.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
84383
102.2 IPS |
|
|
Object Detection (F32)
|
100% |
1492
111.4 IPS |
|
|
Object Detection (F16)
|
100% |
3826
285.7 IPS |
|
|
Object Detection (I8)
|
97% |
1591
118.8 IPS |
|
|
Face Detection (F32)
|
100% |
6275
74.6 IPS |
|
|
Face Detection (F16)
|
97% |
10614
126.2 IPS |
|
|
Face Detection (I8)
|
96% |
10591
125.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
12303
95.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
37358
289.7 IPS |
|
|
Depth Estimation (I8)
|
37% |
36244
281.1 IPS |
|
|
Style Transfer (F32)
|
100% |
28453
37.4 IPS |
|
|
Style Transfer (F16)
|
100% |
122044
160.5 IPS |
|
|
Style Transfer (I8)
|
100% |
120738
158.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6752
241.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18304
653.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
18260
652.1 IPS |
|
|
Text Classification (F32)
|
100% |
457
656.8 IPS |
|
|
Text Classification (F16)
|
100% |
489
703.3 IPS |
|
|
Text Classification (I8)
|
96% |
298
428.3 IPS |
|
|
Machine Translation (F32)
|
100% |
750
13.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1542
28.4 IPS |
|
|
Machine Translation (I8)
|
99% |
687
12.6 IPS |
