iPhone 13 Pro
Geekbench AI Score
3080
Single Precision Score
19271
Half Precision Score
21479
Quantized Score
Geekbench AI 1.4.0 for iOS AArch64
Result Information
| User | Pijiuhua |
| Upload Date | August 12 2025 08:18 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 26.0 |
| Model | iPhone 13 Pro |
| Model ID | iPhone14,2 |
| Motherboard | D63AP |
| CPU Information | |
|---|---|
| Name | Apple A15 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.23 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 5.53 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1359
252.8 IPS |
|
|
Image Classification (HP)
|
100% |
7954
1.48 KIPS |
|
|
Image Classification (Q)
|
96% |
10030
1.87 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1278
20.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
13208
214.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
12917
209.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
5911
6.90 IPS |
|
|
Pose Estimation (HP)
|
100% |
78336
91.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
82184
96.3 IPS |
|
|
Object Detection (SP)
|
100% |
1300
103.1 IPS |
|
|
Object Detection (HP)
|
99% |
10316
820.6 IPS |
|
|
Object Detection (Q)
|
91% |
12109
967.5 IPS |
|
|
Face Detection (SP)
|
100% |
2534
30.1 IPS |
|
|
Face Detection (HP)
|
100% |
26514
315.0 IPS |
|
|
Face Detection (Q)
|
100% |
36682
435.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
5171
39.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
53597
412.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
75224
587.8 IPS |
|
|
Style Transfer (SP)
|
100% |
16135
20.7 IPS |
|
|
Style Transfer (HP)
|
100% |
141642
182.1 IPS |
|
|
Style Transfer (Q)
|
96% |
147388
190.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3588
132.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
29772
1.10 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
28532
1.05 KIPS |
|
|
Text Classification (SP)
|
100% |
2591
3.46 KIPS |
|
|
Text Classification (HP)
|
100% |
2416
3.22 KIPS |
|
|
Text Classification (Q)
|
93% |
2491
3.34 KIPS |
|
|
Machine Translation (SP)
|
100% |
2929
50.5 IPS |
|
|
Machine Translation (HP)
|
100% |
5748
99.0 IPS |
|
|
Machine Translation (Q)
|
98% |
5609
96.9 IPS |
