iPhone 17 Pro
Geekbench AI Score
5122
Single Precision Score
38360
Half Precision Score
52645
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| User | Pijiuhua |
| Upload Date | March 18 2026 09:03 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A19 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.4 |
| Model | iPhone 17 Pro |
| Model ID | iPhone18,1 |
| Motherboard | V53AP |
| CPU Information | |
|---|---|
| Name | Apple A19 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.26 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 11.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2257
419.7 IPS |
|
|
Image Classification (HP)
|
100% |
16665
3.10 KIPS |
|
|
Image Classification (Q)
|
97% |
23271
4.34 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2196
35.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
19424
314.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
24355
394.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
7992
9.33 IPS |
|
|
Pose Estimation (HP)
|
100% |
147537
172.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
277101
324.8 IPS |
|
|
Object Detection (SP)
|
100% |
2552
202.4 IPS |
|
|
Object Detection (HP)
|
100% |
18071
1.43 KIPS |
|
|
Object Detection (Q)
|
89% |
25927
2.08 KIPS |
|
|
Face Detection (SP)
|
100% |
4481
53.2 IPS |
|
|
Face Detection (HP)
|
100% |
42032
499.4 IPS |
|
|
Face Detection (Q)
|
100% |
58263
692.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
7672
59.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
103420
796.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
175657
1.37 KIPS |
|
|
Style Transfer (SP)
|
100% |
20707
26.6 IPS |
|
|
Style Transfer (HP)
|
100% |
252741
324.9 IPS |
|
|
Style Transfer (Q)
|
96% |
326401
421.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4983
184.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
55029
2.03 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
86073
3.18 KIPS |
|
|
Text Classification (SP)
|
100% |
6718
8.97 KIPS |
|
|
Text Classification (HP)
|
100% |
11972
16.0 KIPS |
|
|
Text Classification (Q)
|
93% |
11746
15.8 KIPS |
|
|
Machine Translation (SP)
|
100% |
5166
89.0 IPS |
|
|
Machine Translation (HP)
|
100% |
11047
190.3 IPS |
|
|
Machine Translation (Q)
|
98% |
11893
205.5 IPS |
