iPhone 16 Pro
Geekbench AI Score
4538
Single Precision Score
33177
Half Precision Score
46562
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | robertdb3 |
| Upload Date | May 25 2025 05:16 AM |
| Views | 20 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.5 |
| 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 | 7.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2082
387.1 IPS |
|
|
Image Classification (HP)
|
100% |
15243
2.83 KIPS |
|
|
Image Classification (Q)
|
97% |
19645
3.67 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1981
32.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
18262
296.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
24026
389.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
8840
10.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
147220
171.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
294100
344.7 IPS |
|
|
Object Detection (SP)
|
100% |
2339
185.6 IPS |
|
|
Object Detection (HP)
|
100% |
16285
1.29 KIPS |
|
|
Object Detection (Q)
|
91% |
22392
1.79 KIPS |
|
|
Face Detection (SP)
|
100% |
3877
46.1 IPS |
|
|
Face Detection (HP)
|
100% |
41224
489.8 IPS |
|
|
Face Detection (Q)
|
100% |
59956
712.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
7641
58.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
93876
723.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
163572
1.28 KIPS |
|
|
Style Transfer (SP)
|
100% |
18940
24.3 IPS |
|
|
Style Transfer (HP)
|
100% |
244412
314.2 IPS |
|
|
Style Transfer (Q)
|
96% |
301724
389.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5414
199.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
49890
1.84 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
83782
3.09 KIPS |
|
|
Text Classification (SP)
|
100% |
3374
4.50 KIPS |
|
|
Text Classification (HP)
|
100% |
5075
6.77 KIPS |
|
|
Text Classification (Q)
|
93% |
5346
7.18 KIPS |
|
|
Machine Translation (SP)
|
100% |
4241
73.0 IPS |
|
|
Machine Translation (HP)
|
100% |
10112
174.2 IPS |
|
|
Machine Translation (Q)
|
98% |
11627
200.9 IPS |
