iPhone 13 Pro
Geekbench AI Score
3320
Single Precision Score
19100
Half Precision Score
21768
Quantized Score
Geekbench AI 1.4.0 for iOS AArch64
Result Information
| User | Pijiuhua |
| Upload Date | August 05 2025 10:41 PM |
| Views | 4 |
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% |
1355
252.0 IPS |
|
|
Image Classification (HP)
|
100% |
7414
1.38 KIPS |
|
|
Image Classification (Q)
|
96% |
10598
1.98 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1305
21.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
12315
199.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
14527
235.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
6477
7.56 IPS |
|
|
Pose Estimation (HP)
|
100% |
80164
93.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
81829
95.9 IPS |
|
|
Object Detection (SP)
|
100% |
1439
114.1 IPS |
|
|
Object Detection (HP)
|
99% |
10593
842.7 IPS |
|
|
Object Detection (Q)
|
91% |
12190
974.1 IPS |
|
|
Face Detection (SP)
|
100% |
2707
32.2 IPS |
|
|
Face Detection (HP)
|
100% |
25915
307.9 IPS |
|
|
Face Detection (Q)
|
100% |
33878
402.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
5423
41.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
55456
427.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
68315
533.9 IPS |
|
|
Style Transfer (SP)
|
100% |
17830
22.9 IPS |
|
|
Style Transfer (HP)
|
100% |
144192
185.4 IPS |
|
|
Style Transfer (Q)
|
96% |
142595
184.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3873
143.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
27886
1.03 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
28522
1.05 KIPS |
|
|
Text Classification (SP)
|
100% |
2609
3.48 KIPS |
|
|
Text Classification (HP)
|
100% |
2390
3.19 KIPS |
|
|
Text Classification (Q)
|
93% |
2458
3.30 KIPS |
|
|
Machine Translation (SP)
|
100% |
3740
64.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6037
104.0 IPS |
|
|
Machine Translation (Q)
|
98% |
6724
116.2 IPS |
