iPhone 16 Pro
Geekbench AI Score
4503
Single Precision Score
32979
Half Precision Score
45965
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | mcolsen |
| Upload Date | December 18 2024 12:00 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.2 |
| Model | iPhone 16 Pro |
| Model ID | iPhone17,1 |
| Motherboard | D93AP |
| 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 | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2026
376.8 IPS |
|
|
Image Classification (HP)
|
100% |
15228
2.83 KIPS |
|
|
Image Classification (Q)
|
97% |
20483
3.82 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1909
30.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
18245
295.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
24074
390.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
8490
9.91 IPS |
|
|
Pose Estimation (HP)
|
100% |
152189
177.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
292656
343.0 IPS |
|
|
Object Detection (SP)
|
100% |
2152
170.7 IPS |
|
|
Object Detection (HP)
|
100% |
16206
1.29 KIPS |
|
|
Object Detection (Q)
|
91% |
22438
1.79 KIPS |
|
|
Face Detection (SP)
|
100% |
3633
43.2 IPS |
|
|
Face Detection (HP)
|
100% |
41228
489.9 IPS |
|
|
Face Detection (Q)
|
100% |
58211
691.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
7598
58.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
94970
731.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
161766
1.26 KIPS |
|
|
Style Transfer (SP)
|
100% |
23685
30.4 IPS |
|
|
Style Transfer (HP)
|
100% |
244494
314.3 IPS |
|
|
Style Transfer (Q)
|
96% |
302500
390.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5497
203.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50010
1.85 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
83981
3.10 KIPS |
|
|
Text Classification (SP)
|
100% |
3477
4.64 KIPS |
|
|
Text Classification (HP)
|
100% |
4599
6.14 KIPS |
|
|
Text Classification (Q)
|
93% |
4778
6.41 KIPS |
|
|
Machine Translation (SP)
|
100% |
3883
66.9 IPS |
|
|
Machine Translation (HP)
|
100% |
10087
173.8 IPS |
|
|
Machine Translation (Q)
|
98% |
11377
196.6 IPS |
