iPhone 14 Pro Max
Geekbench AI Score
3422
Single Precision Score
11318
Half Precision Score
14580
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | TTV |
| Upload Date | October 31 2025 01:53 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 26.0.1 |
| Model | iPhone 14 Pro Max |
| Model ID | iPhone15,3 |
| Motherboard | D74AP |
| CPU Information | |
|---|---|
| Name | Apple A16 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.46 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 5.50 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1341
249.3 IPS |
|
|
Image Classification (HP)
|
100% |
4990
928.0 IPS |
|
|
Image Classification (Q)
|
97% |
6299
1.18 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1366
22.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
7484
121.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
14734
238.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
6468
7.55 IPS |
|
|
Pose Estimation (HP)
|
100% |
71579
83.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
66159
77.5 IPS |
|
|
Object Detection (SP)
|
100% |
1451
115.1 IPS |
|
|
Object Detection (HP)
|
100% |
5863
465.0 IPS |
|
|
Object Detection (Q)
|
91% |
7277
581.4 IPS |
|
|
Face Detection (SP)
|
100% |
3088
36.7 IPS |
|
|
Face Detection (HP)
|
100% |
11737
139.5 IPS |
|
|
Face Detection (Q)
|
100% |
19987
237.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
5989
46.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
22015
169.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
27698
216.6 IPS |
|
|
Style Transfer (SP)
|
100% |
18723
24.1 IPS |
|
|
Style Transfer (HP)
|
100% |
97204
125.0 IPS |
|
|
Style Transfer (Q)
|
96% |
149438
192.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3945
145.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
13650
504.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
17408
642.8 IPS |
|
|
Text Classification (SP)
|
100% |
2771
3.70 KIPS |
|
|
Text Classification (HP)
|
100% |
1001
1.34 KIPS |
|
|
Text Classification (Q)
|
93% |
953
1.28 KIPS |
|
|
Machine Translation (SP)
|
100% |
3385
58.3 IPS |
|
|
Machine Translation (HP)
|
100% |
6413
110.5 IPS |
|
|
Machine Translation (Q)
|
98% |
7083
122.4 IPS |
