iPhone 13 Pro Max
Geekbench AI Score
3176
Single Precision Score
20029
Half Precision Score
22245
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | November 22 2025 01:35 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 26.2 |
| 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% |
1265
235.3 IPS |
|
|
Image Classification (HP)
|
100% |
8741
1.63 KIPS |
|
|
Image Classification (Q)
|
96% |
10796
2.02 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1258
20.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
12938
209.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
12623
204.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
6163
7.19 IPS |
|
|
Pose Estimation (HP)
|
100% |
77636
90.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
86816
101.8 IPS |
|
|
Object Detection (SP)
|
100% |
1361
107.9 IPS |
|
|
Object Detection (HP)
|
99% |
11218
892.3 IPS |
|
|
Object Detection (Q)
|
91% |
12094
966.4 IPS |
|
|
Face Detection (SP)
|
100% |
2645
31.4 IPS |
|
|
Face Detection (HP)
|
100% |
26379
313.4 IPS |
|
|
Face Detection (Q)
|
100% |
33166
394.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
5265
40.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
56792
437.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
74269
580.4 IPS |
|
|
Style Transfer (SP)
|
100% |
17438
22.4 IPS |
|
|
Style Transfer (HP)
|
100% |
153436
197.2 IPS |
|
|
Style Transfer (Q)
|
96% |
147511
190.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3648
134.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
28596
1.06 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
30124
1.11 KIPS |
|
|
Text Classification (SP)
|
100% |
2552
3.41 KIPS |
|
|
Text Classification (HP)
|
100% |
2508
3.35 KIPS |
|
|
Text Classification (Q)
|
93% |
2542
3.41 KIPS |
|
|
Machine Translation (SP)
|
100% |
3471
59.8 IPS |
|
|
Machine Translation (HP)
|
100% |
6400
110.2 IPS |
|
|
Machine Translation (Q)
|
98% |
7453
128.8 IPS |
