iPhone 17 Pro
Geekbench AI Score
5370
Single Precision Score
39007
Half Precision Score
53792
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| User | Pijiuhua |
| Upload Date | April 05 2026 06:13 AM |
| Views | 3 |
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% |
2343
435.7 IPS |
|
|
Image Classification (HP)
|
100% |
16328
3.04 KIPS |
|
|
Image Classification (Q)
|
97% |
22745
4.24 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2227
36.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
19965
323.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
26029
421.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
8801
10.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
159438
186.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
298391
349.7 IPS |
|
|
Object Detection (SP)
|
100% |
2750
218.1 IPS |
|
|
Object Detection (HP)
|
100% |
17848
1.42 KIPS |
|
|
Object Detection (Q)
|
89% |
25534
2.04 KIPS |
|
|
Face Detection (SP)
|
100% |
4921
58.5 IPS |
|
|
Face Detection (HP)
|
100% |
41410
492.0 IPS |
|
|
Face Detection (Q)
|
100% |
59426
706.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
8073
62.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
106401
819.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
177367
1.39 KIPS |
|
|
Style Transfer (SP)
|
100% |
22823
29.3 IPS |
|
|
Style Transfer (HP)
|
100% |
263378
338.6 IPS |
|
|
Style Transfer (Q)
|
96% |
328981
424.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4984
184.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
58734
2.17 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
88362
3.26 KIPS |
|
|
Text Classification (SP)
|
99% |
6854
9.15 KIPS |
|
|
Text Classification (HP)
|
100% |
12124
16.2 KIPS |
|
|
Text Classification (Q)
|
93% |
12050
16.2 KIPS |
|
|
Machine Translation (SP)
|
100% |
5105
87.9 IPS |
|
|
Machine Translation (HP)
|
100% |
10639
183.3 IPS |
|
|
Machine Translation (Q)
|
98% |
12182
210.5 IPS |
