iPhone 17
Geekbench AI Score
4522
Single Precision Score
7641
Half Precision Score
6045
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| User | vinebeat |
| Upload Date | March 11 2026 12:54 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A19 |
| System Information | |
|---|---|
| Operating System | iOS 26.3.1 |
| Model | iPhone 17 |
| Model ID | iPhone18,3 |
| Motherboard | V57AP |
| CPU Information | |
|---|---|
| Name | Apple A19 |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.26 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.49 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2152
400.2 IPS |
|
|
Image Classification (HP)
|
100% |
3485
648.0 IPS |
|
|
Image Classification (Q)
|
96% |
2359
440.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1820
29.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2921
47.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
3251
52.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
8268
9.65 IPS |
|
|
Pose Estimation (HP)
|
100% |
17421
20.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
14939
17.5 IPS |
|
|
Object Detection (SP)
|
100% |
2380
188.8 IPS |
|
|
Object Detection (HP)
|
97% |
3903
310.7 IPS |
|
|
Object Detection (Q)
|
94% |
2590
206.4 IPS |
|
|
Face Detection (SP)
|
100% |
3535
42.0 IPS |
|
|
Face Detection (HP)
|
100% |
6976
82.9 IPS |
|
|
Face Detection (Q)
|
100% |
3870
46.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
8006
61.7 IPS |
|
|
Depth Estimation (HP)
|
97% |
13264
102.5 IPS |
|
|
Depth Estimation (Q)
|
86% |
9288
72.5 IPS |
|
|
Style Transfer (SP)
|
100% |
21279
27.4 IPS |
|
|
Style Transfer (HP)
|
100% |
36043
46.3 IPS |
|
|
Style Transfer (Q)
|
96% |
29873
38.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5115
188.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6769
249.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4752
175.5 IPS |
|
|
Text Classification (SP)
|
100% |
3532
4.71 KIPS |
|
|
Text Classification (HP)
|
99% |
6484
8.66 KIPS |
|
|
Text Classification (Q)
|
93% |
6701
8.99 KIPS |
|
|
Machine Translation (SP)
|
100% |
4270
73.6 IPS |
|
|
Machine Translation (HP)
|
98% |
6704
115.8 IPS |
|
|
Machine Translation (Q)
|
98% |
6427
111.1 IPS |
