iPhone 13 Pro Max
Geekbench AI Score
3129
Single Precision Score
20553
Half Precision Score
22997
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | November 05 2025 12:16 AM |
| Views | 1 |
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 Max |
| Model ID | iPhone14,3 |
| Motherboard | D64AP |
| 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 | 5.51 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1260
234.3 IPS |
|
|
Image Classification (HP)
|
100% |
9187
1.71 KIPS |
|
|
Image Classification (Q)
|
96% |
10666
1.99 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1246
20.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
12303
199.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
14536
235.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
5854
6.83 IPS |
|
|
Pose Estimation (HP)
|
100% |
81638
95.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
94308
110.5 IPS |
|
|
Object Detection (SP)
|
100% |
1339
106.2 IPS |
|
|
Object Detection (HP)
|
99% |
11162
887.9 IPS |
|
|
Object Detection (Q)
|
91% |
11403
911.2 IPS |
|
|
Face Detection (SP)
|
100% |
2591
30.8 IPS |
|
|
Face Detection (HP)
|
100% |
29419
349.6 IPS |
|
|
Face Detection (Q)
|
100% |
37664
447.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
5110
39.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
58009
446.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
76318
596.4 IPS |
|
|
Style Transfer (SP)
|
100% |
17119
22.0 IPS |
|
|
Style Transfer (HP)
|
100% |
154356
198.4 IPS |
|
|
Style Transfer (Q)
|
96% |
145495
187.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3681
135.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
29803
1.10 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
30969
1.14 KIPS |
|
|
Text Classification (SP)
|
100% |
2551
3.40 KIPS |
|
|
Text Classification (HP)
|
100% |
2553
3.41 KIPS |
|
|
Text Classification (Q)
|
93% |
2551
3.42 KIPS |
|
|
Machine Translation (SP)
|
100% |
3442
59.3 IPS |
|
|
Machine Translation (HP)
|
100% |
6517
112.3 IPS |
|
|
Machine Translation (Q)
|
98% |
7511
129.8 IPS |
