iPhone 14 Pro Max
Geekbench AI Score
3409
Single Precision Score
17673
Half Precision Score
21351
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | October 30 2025 01:06 AM |
| Views | 3 |
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% |
1334
248.0 IPS |
|
|
Image Classification (HP)
|
100% |
6986
1.30 KIPS |
|
|
Image Classification (Q)
|
97% |
8986
1.68 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1370
22.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
15354
248.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
18977
307.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
6567
7.66 IPS |
|
|
Pose Estimation (HP)
|
100% |
91657
106.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
95868
112.4 IPS |
|
|
Object Detection (SP)
|
100% |
1455
115.4 IPS |
|
|
Object Detection (HP)
|
100% |
7208
571.7 IPS |
|
|
Object Detection (Q)
|
91% |
10447
834.8 IPS |
|
|
Face Detection (SP)
|
100% |
3079
36.6 IPS |
|
|
Face Detection (HP)
|
100% |
29459
350.0 IPS |
|
|
Face Detection (Q)
|
100% |
37919
450.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
5855
45.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
45854
353.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
58863
460.2 IPS |
|
|
Style Transfer (SP)
|
100% |
18658
24.0 IPS |
|
|
Style Transfer (HP)
|
100% |
145026
186.4 IPS |
|
|
Style Transfer (Q)
|
96% |
145904
188.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3850
142.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
17591
649.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
27397
1.01 KIPS |
|
|
Text Classification (SP)
|
100% |
2784
3.72 KIPS |
|
|
Text Classification (HP)
|
100% |
1796
2.40 KIPS |
|
|
Text Classification (Q)
|
93% |
1804
2.42 KIPS |
|
|
Machine Translation (SP)
|
100% |
3374
58.1 IPS |
|
|
Machine Translation (HP)
|
100% |
6778
116.7 IPS |
|
|
Machine Translation (Q)
|
98% |
7165
123.8 IPS |
