iPhone 14 Pro Max
Geekbench AI Score
3500
Single Precision Score
23477
Half Precision Score
27469
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | April 22 2025 02:53 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.4 |
| 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 | 5.51 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1365
253.8 IPS |
|
|
Image Classification (HP)
|
100% |
10800
2.01 KIPS |
|
|
Image Classification (Q)
|
97% |
13368
2.49 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1412
22.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
14355
232.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
19369
314.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
6948
8.11 IPS |
|
|
Pose Estimation (HP)
|
100% |
99995
116.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
104958
123.0 IPS |
|
|
Object Detection (SP)
|
100% |
1564
124.1 IPS |
|
|
Object Detection (HP)
|
100% |
12948
1.03 KIPS |
|
|
Object Detection (Q)
|
91% |
15295
1.22 KIPS |
|
|
Face Detection (SP)
|
100% |
2971
35.3 IPS |
|
|
Face Detection (HP)
|
100% |
31307
372.0 IPS |
|
|
Face Detection (Q)
|
100% |
40054
475.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
6067
46.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
75035
578.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
95997
750.5 IPS |
|
|
Style Transfer (SP)
|
100% |
19037
24.5 IPS |
|
|
Style Transfer (HP)
|
100% |
177297
227.9 IPS |
|
|
Style Transfer (Q)
|
96% |
179980
232.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4106
151.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33133
1.22 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
37616
1.39 KIPS |
|
|
Text Classification (SP)
|
100% |
2691
3.59 KIPS |
|
|
Text Classification (HP)
|
100% |
2426
3.24 KIPS |
|
|
Text Classification (Q)
|
93% |
2680
3.60 KIPS |
|
|
Machine Translation (SP)
|
100% |
3479
59.9 IPS |
|
|
Machine Translation (HP)
|
100% |
7571
130.4 IPS |
|
|
Machine Translation (Q)
|
98% |
8437
145.8 IPS |
