iPhone 17 Pro Max
Geekbench AI Score
9252
Single Precision Score
17521
Half Precision Score
18874
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| User | Moutes |
| Upload Date | March 04 2026 03:48 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Apple A19 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.3 |
| Model | iPhone 17 Pro Max |
| Model ID | iPhone18,2 |
| Motherboard | V54AP |
| CPU Information | |
|---|---|
| Name | Apple A19 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.26 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 11.42 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
4267
793.6 IPS |
|
|
Image Classification (HP)
|
100% |
8501
1.58 KIPS |
|
|
Image Classification (Q)
|
99% |
8758
1.63 KIPS |
|
|
Image Segmentation (SP)
|
100% |
6083
98.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
9574
155.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
10470
169.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
20225
23.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
53742
62.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
67506
79.1 IPS |
|
|
Object Detection (SP)
|
100% |
4405
349.4 IPS |
|
|
Object Detection (HP)
|
100% |
8585
681.0 IPS |
|
|
Object Detection (Q)
|
94% |
9622
767.2 IPS |
|
|
Face Detection (SP)
|
100% |
11872
141.1 IPS |
|
|
Face Detection (HP)
|
100% |
25521
303.2 IPS |
|
|
Face Detection (Q)
|
100% |
24904
295.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
17914
138.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
33435
257.6 IPS |
|
|
Depth Estimation (Q)
|
86% |
37136
289.9 IPS |
|
|
Style Transfer (SP)
|
100% |
44117
56.7 IPS |
|
|
Style Transfer (HP)
|
100% |
95981
123.4 IPS |
|
|
Style Transfer (Q)
|
96% |
124120
160.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
10413
384.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
18792
693.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
21394
790.0 IPS |
|
|
Text Classification (SP)
|
100% |
3458
4.62 KIPS |
|
|
Text Classification (HP)
|
99% |
6308
8.42 KIPS |
|
|
Text Classification (Q)
|
93% |
6266
8.41 KIPS |
|
|
Machine Translation (SP)
|
100% |
5883
101.3 IPS |
|
|
Machine Translation (HP)
|
100% |
7481
128.9 IPS |
|
|
Machine Translation (Q)
|
98% |
6262
108.2 IPS |
