iPhone 13 Pro Max
Geekbench AI Score
1495
Single Precision Score
2643
Half Precision Score
2138
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 20 2025 05:26 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 26.0 |
| 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% |
544
101.1 IPS |
|
|
Image Classification (HP)
|
100% |
1052
195.6 IPS |
|
|
Image Classification (Q)
|
96% |
727
135.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
670
10.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
971
15.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
1121
18.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2719
3.17 IPS |
|
|
Pose Estimation (HP)
|
100% |
6400
7.47 IPS |
|
|
Pose Estimation (Q)
|
95% |
5442
6.38 IPS |
|
|
Object Detection (SP)
|
100% |
583
46.3 IPS |
|
|
Object Detection (HP)
|
97% |
1187
94.5 IPS |
|
|
Object Detection (Q)
|
94% |
842
67.1 IPS |
|
|
Face Detection (SP)
|
100% |
1531
18.2 IPS |
|
|
Face Detection (HP)
|
100% |
2543
30.2 IPS |
|
|
Face Detection (Q)
|
100% |
1453
17.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
2256
17.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
4500
34.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
3145
24.6 IPS |
|
|
Style Transfer (SP)
|
100% |
7665
9.85 IPS |
|
|
Style Transfer (HP)
|
100% |
12088
15.5 IPS |
|
|
Style Transfer (Q)
|
96% |
10063
13.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1678
62.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2179
80.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1641
60.6 IPS |
|
|
Text Classification (SP)
|
100% |
1217
1.62 KIPS |
|
|
Text Classification (HP)
|
99% |
2099
2.80 KIPS |
|
|
Text Classification (Q)
|
93% |
2087
2.80 KIPS |
|
|
Machine Translation (SP)
|
100% |
1795
30.9 IPS |
|
|
Machine Translation (HP)
|
98% |
3397
58.7 IPS |
|
|
Machine Translation (Q)
|
98% |
3409
58.9 IPS |
