iPhone 16 Pro
Geekbench AI Score
5985
Single Precision Score
7099
Half Precision Score
6753
Quantized Score
Geekbench AI 1.4.0 for iOS AArch64
Result Information
| User | VenomF5 |
| Upload Date | July 25 2025 12:30 AM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.0 |
| 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% |
2909
540.9 IPS |
|
|
Image Classification (HP)
|
100% |
2800
520.7 IPS |
|
|
Image Classification (Q)
|
96% |
2991
558.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
4420
71.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
4928
79.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
4739
76.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
15158
17.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
18004
21.0 IPS |
|
|
Pose Estimation (Q)
|
96% |
17196
20.1 IPS |
|
|
Object Detection (SP)
|
100% |
3186
252.7 IPS |
|
|
Object Detection (HP)
|
100% |
3352
265.9 IPS |
|
|
Object Detection (Q)
|
92% |
3408
272.1 IPS |
|
|
Face Detection (SP)
|
100% |
7344
87.3 IPS |
|
|
Face Detection (HP)
|
100% |
10496
124.7 IPS |
|
|
Face Detection (Q)
|
100% |
8520
101.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
13008
100.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
15635
120.5 IPS |
|
|
Depth Estimation (Q)
|
86% |
13971
109.1 IPS |
|
|
Style Transfer (SP)
|
100% |
31336
40.3 IPS |
|
|
Style Transfer (HP)
|
100% |
39209
50.4 IPS |
|
|
Style Transfer (Q)
|
96% |
38687
49.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
7510
277.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
8285
305.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
7086
261.7 IPS |
|
|
Text Classification (SP)
|
100% |
3598
4.80 KIPS |
|
|
Text Classification (HP)
|
99% |
5898
7.87 KIPS |
|
|
Text Classification (Q)
|
93% |
5957
7.99 KIPS |
|
|
Machine Translation (SP)
|
100% |
1175
20.2 IPS |
|
|
Machine Translation (HP)
|
100% |
1243
21.4 IPS |
|
|
Machine Translation (Q)
|
98% |
1223
21.1 IPS |
