iPhone 13 Pro
Geekbench AI Score
3268
Single Precision Score
18778
Half Precision Score
21576
Quantized Score
Geekbench AI 1.4.0 for iOS AArch64
Result Information
| User | Pijiuhua |
| Upload Date | September 02 2025 08:26 AM |
| Views | 2 |
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% |
1344
250.0 IPS |
|
|
Image Classification (HP)
|
100% |
7515
1.40 KIPS |
|
|
Image Classification (Q)
|
96% |
10637
1.99 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1285
20.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
13227
214.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
13805
223.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
6203
7.24 IPS |
|
|
Pose Estimation (HP)
|
100% |
77325
90.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
81790
95.9 IPS |
|
|
Object Detection (SP)
|
100% |
1447
114.7 IPS |
|
|
Object Detection (HP)
|
99% |
9832
782.1 IPS |
|
|
Object Detection (Q)
|
91% |
11432
913.5 IPS |
|
|
Face Detection (SP)
|
100% |
2696
32.0 IPS |
|
|
Face Detection (HP)
|
100% |
26471
314.5 IPS |
|
|
Face Detection (Q)
|
100% |
36298
431.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
5368
41.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
52590
405.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
74578
582.8 IPS |
|
|
Style Transfer (SP)
|
100% |
17384
22.3 IPS |
|
|
Style Transfer (HP)
|
100% |
148164
190.5 IPS |
|
|
Style Transfer (Q)
|
96% |
140462
181.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3816
140.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
26952
995.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
27704
1.02 KIPS |
|
|
Text Classification (SP)
|
100% |
2538
3.39 KIPS |
|
|
Text Classification (HP)
|
100% |
2170
2.90 KIPS |
|
|
Text Classification (Q)
|
93% |
2248
3.02 KIPS |
|
|
Machine Translation (SP)
|
100% |
3685
63.5 IPS |
|
|
Machine Translation (HP)
|
100% |
5982
103.0 IPS |
|
|
Machine Translation (Q)
|
98% |
6725
116.2 IPS |
