iPhone 13 Pro Max
Geekbench AI Score
3265
Single Precision Score
19245
Half Precision Score
22219
Quantized Score
Geekbench AI 1.4.0 for iOS AArch64
Result Information
| Upload Date | August 26 2025 10:00 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.6.1 |
| 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% |
1348
250.7 IPS |
|
|
Image Classification (HP)
|
100% |
8109
1.51 KIPS |
|
|
Image Classification (Q)
|
96% |
9214
1.72 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1274
20.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
12721
206.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
14811
240.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
6388
7.45 IPS |
|
|
Pose Estimation (HP)
|
100% |
88883
103.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
94493
110.8 IPS |
|
|
Object Detection (SP)
|
100% |
1443
114.4 IPS |
|
|
Object Detection (HP)
|
99% |
10385
826.1 IPS |
|
|
Object Detection (Q)
|
91% |
12148
970.7 IPS |
|
|
Face Detection (SP)
|
100% |
2658
31.6 IPS |
|
|
Face Detection (HP)
|
100% |
29380
349.1 IPS |
|
|
Face Detection (Q)
|
100% |
36998
439.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
5339
41.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
56256
433.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
75588
590.7 IPS |
|
|
Style Transfer (SP)
|
100% |
17751
22.8 IPS |
|
|
Style Transfer (HP)
|
100% |
150148
193.0 IPS |
|
|
Style Transfer (Q)
|
96% |
148962
192.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3848
142.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
27219
1.01 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
30358
1.12 KIPS |
|
|
Text Classification (SP)
|
100% |
2472
3.30 KIPS |
|
|
Text Classification (HP)
|
100% |
1771
2.36 KIPS |
|
|
Text Classification (Q)
|
93% |
2120
2.85 KIPS |
|
|
Machine Translation (SP)
|
100% |
3638
62.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6120
105.4 IPS |
|
|
Machine Translation (Q)
|
98% |
6985
120.7 IPS |
