iPhone 13 Pro Max
Geekbench AI Score
3133
Single Precision Score
19702
Half Precision Score
21759
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| User | Matso |
| Upload Date | March 11 2026 02:14 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 26.3.1 |
| 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% |
1279
237.8 IPS |
|
|
Image Classification (HP)
|
100% |
7297
1.36 KIPS |
|
|
Image Classification (Q)
|
96% |
10366
1.94 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1242
20.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
13274
215.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
12863
208.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
5814
6.78 IPS |
|
|
Pose Estimation (HP)
|
100% |
79611
92.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
80968
94.9 IPS |
|
|
Object Detection (SP)
|
100% |
1344
106.6 IPS |
|
|
Object Detection (HP)
|
99% |
10703
851.4 IPS |
|
|
Object Detection (Q)
|
91% |
12419
992.3 IPS |
|
|
Face Detection (SP)
|
100% |
2608
31.0 IPS |
|
|
Face Detection (HP)
|
100% |
29195
346.9 IPS |
|
|
Face Detection (Q)
|
100% |
37608
446.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
5085
39.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
55871
430.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
69464
542.8 IPS |
|
|
Style Transfer (SP)
|
100% |
16968
21.8 IPS |
|
|
Style Transfer (HP)
|
100% |
150091
192.9 IPS |
|
|
Style Transfer (Q)
|
96% |
144979
187.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3686
136.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
29864
1.10 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
28448
1.05 KIPS |
|
|
Text Classification (SP)
|
100% |
2575
3.44 KIPS |
|
|
Text Classification (HP)
|
100% |
2362
3.15 KIPS |
|
|
Text Classification (Q)
|
93% |
2417
3.24 KIPS |
|
|
Machine Translation (SP)
|
100% |
3445
59.3 IPS |
|
|
Machine Translation (HP)
|
100% |
6185
106.5 IPS |
|
|
Machine Translation (Q)
|
98% |
6815
117.8 IPS |
