iPhone 15 Pro Max
Geekbench AI Score
3953
Single Precision Score
6841
Half Precision Score
5596
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | VenomF5 |
| Upload Date | September 25 2024 10:39 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| 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% |
1717
319.3 IPS |
|
|
Image Classification (HP)
|
100% |
2938
546.3 IPS |
|
|
Image Classification (Q)
|
96% |
2013
375.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1612
26.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2404
39.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
3076
49.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
8137
9.49 IPS |
|
|
Pose Estimation (HP)
|
100% |
16587
19.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
14446
16.9 IPS |
|
|
Object Detection (SP)
|
100% |
1798
142.6 IPS |
|
|
Object Detection (HP)
|
97% |
3338
265.8 IPS |
|
|
Object Detection (Q)
|
94% |
2345
186.9 IPS |
|
|
Face Detection (SP)
|
100% |
3204
38.1 IPS |
|
|
Face Detection (HP)
|
100% |
6762
80.4 IPS |
|
|
Face Detection (Q)
|
100% |
3879
46.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
7052
54.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
13519
104.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
9315
72.8 IPS |
|
|
Style Transfer (SP)
|
100% |
21084
27.1 IPS |
|
|
Style Transfer (HP)
|
100% |
32407
41.7 IPS |
|
|
Style Transfer (Q)
|
96% |
27318
35.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4875
180.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5862
216.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4402
162.5 IPS |
|
|
Text Classification (SP)
|
100% |
3199
4.27 KIPS |
|
|
Text Classification (HP)
|
100% |
5492
7.33 KIPS |
|
|
Text Classification (Q)
|
93% |
5488
7.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
3100
53.4 IPS |
|
|
Machine Translation (HP)
|
98% |
6024
104.1 IPS |
|
|
Machine Translation (Q)
|
98% |
6028
104.2 IPS |
