iPhone 14 Pro Max
Geekbench AI Score
3420
Single Precision Score
16315
Half Precision Score
19428
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | TTV |
| Upload Date | September 27 2025 06:54 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 26.0 |
| 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% |
1321
245.7 IPS |
|
|
Image Classification (HP)
|
100% |
6424
1.19 KIPS |
|
|
Image Classification (Q)
|
97% |
7662
1.43 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1361
22.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
13866
224.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
18329
297.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
6604
7.71 IPS |
|
|
Pose Estimation (HP)
|
100% |
87207
101.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
92323
108.2 IPS |
|
|
Object Detection (SP)
|
100% |
1467
116.4 IPS |
|
|
Object Detection (HP)
|
100% |
6260
496.6 IPS |
|
|
Object Detection (Q)
|
91% |
9105
727.6 IPS |
|
|
Face Detection (SP)
|
100% |
3114
37.0 IPS |
|
|
Face Detection (HP)
|
100% |
27083
321.8 IPS |
|
|
Face Detection (Q)
|
100% |
33822
401.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
5907
45.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
36546
281.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
60854
475.8 IPS |
|
|
Style Transfer (SP)
|
100% |
18778
24.1 IPS |
|
|
Style Transfer (HP)
|
100% |
143440
184.4 IPS |
|
|
Style Transfer (Q)
|
96% |
139470
180.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3868
142.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
17530
647.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
21423
791.0 IPS |
|
|
Text Classification (SP)
|
100% |
2787
3.72 KIPS |
|
|
Text Classification (HP)
|
100% |
1613
2.15 KIPS |
|
|
Text Classification (Q)
|
93% |
1524
2.05 KIPS |
|
|
Machine Translation (SP)
|
100% |
3383
58.3 IPS |
|
|
Machine Translation (HP)
|
100% |
6847
117.9 IPS |
|
|
Machine Translation (Q)
|
98% |
6927
119.7 IPS |
