iPhone 16 Pro
Geekbench AI Score
4569
Single Precision Score
33706
Half Precision Score
45582
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| User | ARSCON |
| Upload Date | February 18 2026 08:05 AM |
| Views | 12 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.3 |
| 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% |
2008
373.5 IPS |
|
|
Image Classification (HP)
|
100% |
14696
2.73 KIPS |
|
|
Image Classification (Q)
|
97% |
19112
3.57 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1818
29.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
18070
292.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
23647
383.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
8771
10.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
152795
178.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
291709
341.9 IPS |
|
|
Object Detection (SP)
|
100% |
2308
183.1 IPS |
|
|
Object Detection (HP)
|
100% |
16399
1.30 KIPS |
|
|
Object Detection (Q)
|
91% |
21942
1.75 KIPS |
|
|
Face Detection (SP)
|
100% |
3329
39.6 IPS |
|
|
Face Detection (HP)
|
100% |
40660
483.1 IPS |
|
|
Face Detection (Q)
|
100% |
54269
644.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
8094
62.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
94195
725.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
156027
1.22 KIPS |
|
|
Style Transfer (SP)
|
100% |
22713
29.2 IPS |
|
|
Style Transfer (HP)
|
100% |
245719
315.9 IPS |
|
|
Style Transfer (Q)
|
96% |
294773
380.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5595
206.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
52171
1.93 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
82102
3.03 KIPS |
|
|
Text Classification (SP)
|
100% |
3734
4.98 KIPS |
|
|
Text Classification (HP)
|
99% |
6251
8.34 KIPS |
|
|
Text Classification (Q)
|
93% |
6234
8.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
4204
72.4 IPS |
|
|
Machine Translation (HP)
|
100% |
9269
159.7 IPS |
|
|
Machine Translation (Q)
|
98% |
10479
181.1 IPS |
