iPhone 13 Pro Max
Geekbench AI Score
3174
Single Precision Score
19726
Half Precision Score
23166
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | November 05 2025 08:17 PM |
| 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% |
1250
232.5 IPS |
|
|
Image Classification (HP)
|
100% |
7344
1.37 KIPS |
|
|
Image Classification (Q)
|
96% |
11345
2.12 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1245
20.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
12107
196.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
15273
247.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
6116
7.14 IPS |
|
|
Pose Estimation (HP)
|
100% |
85934
100.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
94425
110.7 IPS |
|
|
Object Detection (SP)
|
100% |
1368
108.5 IPS |
|
|
Object Detection (HP)
|
99% |
10789
858.3 IPS |
|
|
Object Detection (Q)
|
91% |
12180
973.2 IPS |
|
|
Face Detection (SP)
|
100% |
2604
30.9 IPS |
|
|
Face Detection (HP)
|
100% |
26225
311.6 IPS |
|
|
Face Detection (Q)
|
100% |
37823
449.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
5215
40.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
58295
449.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
77656
606.8 IPS |
|
|
Style Transfer (SP)
|
100% |
17468
22.5 IPS |
|
|
Style Transfer (HP)
|
100% |
155742
200.2 IPS |
|
|
Style Transfer (Q)
|
96% |
151225
195.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3739
138.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
29903
1.10 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
29399
1.09 KIPS |
|
|
Text Classification (SP)
|
100% |
2600
3.47 KIPS |
|
|
Text Classification (HP)
|
100% |
2495
3.33 KIPS |
|
|
Text Classification (Q)
|
93% |
2451
3.29 KIPS |
|
|
Machine Translation (SP)
|
100% |
3466
59.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6094
105.0 IPS |
|
|
Machine Translation (Q)
|
98% |
6980
120.6 IPS |
