iPhone 16 Pro Max
Geekbench AI Score
5771
Single Precision Score
6790
Half Precision Score
6014
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | Farzad |
| Upload Date | February 19 2025 10:09 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.3.1 |
| Model | iPhone 16 Pro Max |
| Model ID | iPhone17,2 |
| Motherboard | D94AP |
| CPU Information | |
|---|---|
| Name | Apple A18 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.04 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2880
535.7 IPS |
|
|
Image Classification (HP)
|
100% |
2806
521.9 IPS |
|
|
Image Classification (Q)
|
97% |
2872
535.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
3353
54.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
4434
71.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
4392
71.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
15657
18.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
16490
19.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
15497
18.2 IPS |
|
|
Object Detection (SP)
|
100% |
3185
252.6 IPS |
|
|
Object Detection (HP)
|
100% |
3469
275.1 IPS |
|
|
Object Detection (Q)
|
91% |
2861
228.6 IPS |
|
|
Face Detection (SP)
|
100% |
7638
90.8 IPS |
|
|
Face Detection (HP)
|
100% |
10722
127.4 IPS |
|
|
Face Detection (Q)
|
100% |
7174
85.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
13636
105.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
14416
111.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
12237
95.7 IPS |
|
|
Style Transfer (SP)
|
100% |
33141
42.6 IPS |
|
|
Style Transfer (HP)
|
100% |
39543
50.8 IPS |
|
|
Style Transfer (Q)
|
96% |
36182
46.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
7964
294.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
8428
311.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
6710
247.8 IPS |
|
|
Text Classification (SP)
|
100% |
3417
4.56 KIPS |
|
|
Text Classification (HP)
|
100% |
5859
7.82 KIPS |
|
|
Text Classification (Q)
|
93% |
5823
7.82 KIPS |
|
|
Machine Translation (SP)
|
100% |
906
15.6 IPS |
|
|
Machine Translation (HP)
|
100% |
971
16.7 IPS |
|
|
Machine Translation (Q)
|
98% |
893
15.4 IPS |
