iPhone 16 Pro
Geekbench AI Score
6067
Single Precision Score
7221
Half Precision Score
6810
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | VenomF5 |
| Upload Date | October 01 2025 04:53 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.0.1 |
| 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 | 7.46 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2827
525.7 IPS |
|
|
Image Classification (HP)
|
100% |
2633
489.6 IPS |
|
|
Image Classification (Q)
|
96% |
3096
578.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
4466
72.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
4930
79.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
4761
77.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
15215
17.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
17985
21.0 IPS |
|
|
Pose Estimation (Q)
|
96% |
17184
20.1 IPS |
|
|
Object Detection (SP)
|
100% |
3222
255.5 IPS |
|
|
Object Detection (HP)
|
100% |
3672
291.3 IPS |
|
|
Object Detection (Q)
|
92% |
3334
266.1 IPS |
|
|
Face Detection (SP)
|
100% |
7307
86.8 IPS |
|
|
Face Detection (HP)
|
100% |
10680
126.9 IPS |
|
|
Face Detection (Q)
|
100% |
8571
101.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
13109
101.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
15503
119.4 IPS |
|
|
Depth Estimation (Q)
|
86% |
13735
107.3 IPS |
|
|
Style Transfer (SP)
|
100% |
32542
41.8 IPS |
|
|
Style Transfer (HP)
|
100% |
41013
52.7 IPS |
|
|
Style Transfer (Q)
|
96% |
39752
51.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
7803
288.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
8466
312.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
7372
272.2 IPS |
|
|
Text Classification (SP)
|
100% |
3694
4.93 KIPS |
|
|
Text Classification (HP)
|
99% |
6102
8.14 KIPS |
|
|
Text Classification (Q)
|
93% |
6062
8.14 KIPS |
|
|
Machine Translation (SP)
|
100% |
1217
21.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1283
22.1 IPS |
|
|
Machine Translation (Q)
|
98% |
1215
21.0 IPS |
