iPhone 13 Pro Max
Geekbench AI Score
3260
Single Precision Score
16413
Half Precision Score
18191
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 17 2024 10:20 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A15 Bionic |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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% |
1327
246.8 IPS |
|
|
Image Classification (HP)
|
100% |
8484
1.58 KIPS |
|
|
Image Classification (Q)
|
96% |
9654
1.80 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1302
21.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
6907
112.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
7248
117.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
6396
7.46 IPS |
|
|
Pose Estimation (HP)
|
100% |
85160
99.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
93786
109.9 IPS |
|
|
Object Detection (SP)
|
100% |
1448
114.8 IPS |
|
|
Object Detection (HP)
|
99% |
10595
842.8 IPS |
|
|
Object Detection (Q)
|
91% |
11682
933.5 IPS |
|
|
Face Detection (SP)
|
100% |
2701
32.1 IPS |
|
|
Face Detection (HP)
|
100% |
25012
297.2 IPS |
|
|
Face Detection (Q)
|
100% |
31029
368.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
5512
42.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
53430
411.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
71670
560.1 IPS |
|
|
Style Transfer (SP)
|
100% |
17698
22.8 IPS |
|
|
Style Transfer (HP)
|
100% |
151383
194.6 IPS |
|
|
Style Transfer (Q)
|
96% |
151575
195.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3954
146.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
26133
965.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
28586
1.06 KIPS |
|
|
Text Classification (SP)
|
100% |
2383
3.18 KIPS |
|
|
Text Classification (HP)
|
100% |
2283
3.05 KIPS |
|
|
Text Classification (Q)
|
93% |
2397
3.22 KIPS |
|
|
Machine Translation (SP)
|
100% |
3419
58.9 IPS |
|
|
Machine Translation (HP)
|
100% |
2224
38.3 IPS |
|
|
Machine Translation (Q)
|
98% |
2241
38.7 IPS |
