iPhone 15 Pro Max
Geekbench AI Score
4014
Single Precision Score
24850
Half Precision Score
34766
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | November 19 2024 03:02 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| 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 |
| Memory Information | |
|---|---|
| Size | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1716
319.1 IPS |
|
|
Image Classification (HP)
|
100% |
11453
2.13 KIPS |
|
|
Image Classification (Q)
|
97% |
15083
2.81 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1682
27.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
15739
255.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
20908
338.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
8429
9.84 IPS |
|
|
Pose Estimation (HP)
|
100% |
106371
124.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
204064
239.2 IPS |
|
|
Object Detection (SP)
|
100% |
1781
141.2 IPS |
|
|
Object Detection (HP)
|
100% |
13601
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
19049
1.52 KIPS |
|
|
Face Detection (SP)
|
100% |
3148
37.4 IPS |
|
|
Face Detection (HP)
|
100% |
33941
403.3 IPS |
|
|
Face Detection (Q)
|
100% |
50495
600.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
7174
55.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
78335
603.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
126270
987.2 IPS |
|
|
Style Transfer (SP)
|
100% |
21614
27.8 IPS |
|
|
Style Transfer (HP)
|
100% |
203554
261.7 IPS |
|
|
Style Transfer (Q)
|
96% |
247516
319.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5111
188.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33739
1.25 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57629
2.13 KIPS |
|
|
Text Classification (SP)
|
100% |
3236
4.32 KIPS |
|
|
Text Classification (HP)
|
100% |
3084
4.12 KIPS |
|
|
Text Classification (Q)
|
93% |
3188
4.28 KIPS |
|
|
Machine Translation (SP)
|
100% |
3108
53.5 IPS |
|
|
Machine Translation (HP)
|
100% |
6115
105.3 IPS |
|
|
Machine Translation (Q)
|
98% |
7259
125.4 IPS |
