iPhone 13 Pro
Geekbench AI Score
3070
Single Precision Score
18460
Half Precision Score
20676
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | Pijiuhua |
| Upload Date | December 04 2025 09:49 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 26.1 |
| 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% |
1260
234.3 IPS |
|
|
Image Classification (HP)
|
100% |
7965
1.48 KIPS |
|
|
Image Classification (Q)
|
96% |
10553
1.97 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1264
20.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
12684
205.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
12228
198.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
5398
6.30 IPS |
|
|
Pose Estimation (HP)
|
100% |
55518
64.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
66020
77.4 IPS |
|
|
Object Detection (SP)
|
100% |
1190
94.4 IPS |
|
|
Object Detection (HP)
|
99% |
8950
711.9 IPS |
|
|
Object Detection (Q)
|
91% |
10240
818.2 IPS |
|
|
Face Detection (SP)
|
100% |
2528
30.0 IPS |
|
|
Face Detection (HP)
|
100% |
25465
302.6 IPS |
|
|
Face Detection (Q)
|
100% |
35764
425.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
5130
39.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
57188
440.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
66369
518.6 IPS |
|
|
Style Transfer (SP)
|
100% |
17041
21.9 IPS |
|
|
Style Transfer (HP)
|
100% |
152457
196.0 IPS |
|
|
Style Transfer (Q)
|
96% |
141758
182.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3747
138.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
27623
1.02 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
29789
1.10 KIPS |
|
|
Text Classification (SP)
|
100% |
2573
3.43 KIPS |
|
|
Text Classification (HP)
|
100% |
2469
3.29 KIPS |
|
|
Text Classification (Q)
|
93% |
2398
3.22 KIPS |
|
|
Machine Translation (SP)
|
100% |
3416
58.8 IPS |
|
|
Machine Translation (HP)
|
100% |
6047
104.2 IPS |
|
|
Machine Translation (Q)
|
98% |
6812
117.7 IPS |
