trelf's iPhizzle Pro Mizzle 16 iPhone 16 Pro Max
Geekbench AI Score
4493
Single Precision Score
7706
Half Precision Score
6162
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | trelf |
| Upload Date | December 25 2024 09:17 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.2 |
| Model | iPhone 16 Pro Max |
| Model ID | iPhone17,2 |
| Motherboard | D94AP |
| CPU Information | |
|---|---|
| Name | Apple A18 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.04 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1994
370.9 IPS |
|
|
Image Classification (HP)
|
100% |
3368
626.3 IPS |
|
|
Image Classification (Q)
|
96% |
2278
425.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1932
31.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2893
46.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
3373
54.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
8752
10.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
18091
21.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
15380
18.0 IPS |
|
|
Object Detection (SP)
|
100% |
2138
169.6 IPS |
|
|
Object Detection (HP)
|
97% |
3769
300.1 IPS |
|
|
Object Detection (Q)
|
94% |
2675
213.2 IPS |
|
|
Face Detection (SP)
|
100% |
3558
42.3 IPS |
|
|
Face Detection (HP)
|
100% |
7437
88.4 IPS |
|
|
Face Detection (Q)
|
100% |
4187
49.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
7682
59.2 IPS |
|
|
Depth Estimation (HP)
|
97% |
14033
108.5 IPS |
|
|
Depth Estimation (Q)
|
86% |
9721
75.9 IPS |
|
|
Style Transfer (SP)
|
100% |
23720
30.5 IPS |
|
|
Style Transfer (HP)
|
100% |
37408
48.1 IPS |
|
|
Style Transfer (Q)
|
96% |
30390
39.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5536
204.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6920
255.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4936
182.3 IPS |
|
|
Text Classification (SP)
|
100% |
3419
4.56 KIPS |
|
|
Text Classification (HP)
|
100% |
5853
7.81 KIPS |
|
|
Text Classification (Q)
|
93% |
5829
7.82 KIPS |
|
|
Machine Translation (SP)
|
100% |
3790
65.3 IPS |
|
|
Machine Translation (HP)
|
98% |
7032
121.5 IPS |
|
|
Machine Translation (Q)
|
98% |
7022
121.3 IPS |
