iPhone 17 Pro
Geekbench AI Score
5242
Single Precision Score
38740
Half Precision Score
53089
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| User | Pijiuhua |
| Upload Date | April 04 2026 05:50 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A19 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.5 |
| 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% |
2217
412.3 IPS |
|
|
Image Classification (HP)
|
100% |
16349
3.04 KIPS |
|
|
Image Classification (Q)
|
97% |
23062
4.30 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2138
34.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
19838
321.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
25207
408.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
8174
9.54 IPS |
|
|
Pose Estimation (HP)
|
100% |
151985
177.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
285640
334.8 IPS |
|
|
Object Detection (SP)
|
100% |
2704
214.5 IPS |
|
|
Object Detection (HP)
|
100% |
17646
1.40 KIPS |
|
|
Object Detection (Q)
|
89% |
25709
2.06 KIPS |
|
|
Face Detection (SP)
|
100% |
4833
57.4 IPS |
|
|
Face Detection (HP)
|
100% |
43194
513.2 IPS |
|
|
Face Detection (Q)
|
100% |
58242
692.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
7865
60.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
104934
808.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
180994
1.41 KIPS |
|
|
Style Transfer (SP)
|
100% |
21824
28.1 IPS |
|
|
Style Transfer (HP)
|
100% |
260515
334.9 IPS |
|
|
Style Transfer (Q)
|
96% |
328354
423.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5145
190.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
56968
2.10 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
85288
3.15 KIPS |
|
|
Text Classification (SP)
|
99% |
6712
8.96 KIPS |
|
|
Text Classification (HP)
|
100% |
11504
15.4 KIPS |
|
|
Text Classification (Q)
|
93% |
11413
15.3 KIPS |
|
|
Machine Translation (SP)
|
100% |
5221
89.9 IPS |
|
|
Machine Translation (HP)
|
100% |
11312
194.9 IPS |
|
|
Machine Translation (Q)
|
98% |
12366
213.7 IPS |
