iPhone 15 Pro Max
Geekbench AI Score
3943
Single Precision Score
24078
Half Precision Score
33580
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 17 2024 11:09 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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% |
1710
318.0 IPS |
|
|
Image Classification (HP)
|
100% |
11012
2.05 KIPS |
|
|
Image Classification (Q)
|
97% |
15172
2.83 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1614
26.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
12882
208.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
16020
259.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
7989
9.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
107026
124.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
203262
238.2 IPS |
|
|
Object Detection (SP)
|
100% |
1795
142.4 IPS |
|
|
Object Detection (HP)
|
100% |
13722
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
19076
1.52 KIPS |
|
|
Face Detection (SP)
|
100% |
3140
37.3 IPS |
|
|
Face Detection (HP)
|
100% |
33593
399.2 IPS |
|
|
Face Detection (Q)
|
100% |
49454
587.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
7113
54.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
78877
607.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
128161
1.00 KIPS |
|
|
Style Transfer (SP)
|
100% |
21095
27.1 IPS |
|
|
Style Transfer (HP)
|
100% |
203141
261.1 IPS |
|
|
Style Transfer (Q)
|
96% |
249204
321.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4933
182.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34416
1.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55113
2.04 KIPS |
|
|
Text Classification (SP)
|
100% |
3189
4.26 KIPS |
|
|
Text Classification (HP)
|
100% |
2735
3.65 KIPS |
|
|
Text Classification (Q)
|
93% |
2954
3.97 KIPS |
|
|
Machine Translation (SP)
|
100% |
3103
53.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6207
106.9 IPS |
|
|
Machine Translation (Q)
|
98% |
7524
130.0 IPS |
