iPhone 14 Pro Max
Geekbench AI Score
2370
Single Precision Score
12757
Half Precision Score
13852
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | ranzi |
| Upload Date | August 15 2024 09:39 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A16 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| 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 | 5.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1227
228.2 IPS |
|
|
Image Classification (HP)
|
100% |
5764
1.07 KIPS |
|
|
Image Classification (Q)
|
99% |
6004
1.12 KIPS |
|
|
Image Segmentation (SP)
|
100% |
750
12.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
5034
81.6 IPS |
|
|
Image Segmentation (Q)
|
100% |
5110
82.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
6400
7.47 IPS |
|
|
Pose Estimation (HP)
|
100% |
78226
91.3 IPS |
|
|
Pose Estimation (Q)
|
94% |
84815
99.5 IPS |
|
|
Object Detection (SP)
|
100% |
1306
103.6 IPS |
|
|
Object Detection (HP)
|
100% |
7538
598.0 IPS |
|
|
Object Detection (Q)
|
93% |
8380
668.6 IPS |
|
|
Face Detection (SP)
|
100% |
2183
25.9 IPS |
|
|
Face Detection (HP)
|
100% |
10611
126.1 IPS |
|
|
Face Detection (Q)
|
100% |
12520
148.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
4115
31.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
40807
314.4 IPS |
|
|
Depth Estimation (Q)
|
97% |
45101
348.7 IPS |
|
|
Style Transfer (SP)
|
100% |
11101
14.3 IPS |
|
|
Style Transfer (HP)
|
100% |
121393
156.1 IPS |
|
|
Style Transfer (Q)
|
100% |
121228
155.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3238
119.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
16715
617.2 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
21448
794.6 IPS |
|
|
Text Classification (SP)
|
100% |
1378
1.84 KIPS |
|
|
Text Classification (HP)
|
100% |
3299
4.40 KIPS |
|
|
Text Classification (Q)
|
93% |
3503
4.70 KIPS |
|
|
Machine Translation (SP)
|
100% |
1636
28.2 IPS |
|
|
Machine Translation (HP)
|
100% |
2302
39.7 IPS |
|
|
Machine Translation (Q)
|
98% |
2320
40.1 IPS |
