iPhone 13 Pro Max
Geekbench AI Score
3159
Single Precision Score
18397
Half Precision Score
20552
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | November 07 2025 04:03 AM |
| Views | 4 |
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% |
7534
1.40 KIPS |
|
|
Image Classification (Q)
|
96% |
9220
1.72 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1254
20.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
12739
206.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
14602
236.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
6024
7.03 IPS |
|
|
Pose Estimation (HP)
|
100% |
78069
91.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
81576
95.6 IPS |
|
|
Object Detection (SP)
|
100% |
1356
107.5 IPS |
|
|
Object Detection (HP)
|
99% |
10233
814.0 IPS |
|
|
Object Detection (Q)
|
91% |
11854
947.2 IPS |
|
|
Face Detection (SP)
|
100% |
2578
30.6 IPS |
|
|
Face Detection (HP)
|
100% |
24788
294.5 IPS |
|
|
Face Detection (Q)
|
100% |
32872
390.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
5145
39.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
58475
450.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
66206
517.4 IPS |
|
|
Style Transfer (SP)
|
100% |
17423
22.4 IPS |
|
|
Style Transfer (HP)
|
100% |
142961
183.8 IPS |
|
|
Style Transfer (Q)
|
96% |
136271
175.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3696
136.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
29508
1.09 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
28048
1.04 KIPS |
|
|
Text Classification (SP)
|
100% |
2594
3.46 KIPS |
|
|
Text Classification (HP)
|
100% |
1531
2.04 KIPS |
|
|
Text Classification (Q)
|
93% |
1759
2.36 KIPS |
|
|
Machine Translation (SP)
|
100% |
3470
59.8 IPS |
|
|
Machine Translation (HP)
|
100% |
6190
106.6 IPS |
|
|
Machine Translation (Q)
|
98% |
7058
122.0 IPS |
