iPhone 15 Pro Max
Geekbench AI Score
3793
Single Precision Score
24604
Half Precision Score
33703
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | November 20 2024 05:19 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| Model | iPhone 15 Pro Max |
| Model ID | iPhone16,2 |
| Motherboard | D84AP |
| CPU Information | |
|---|---|
| Name | Apple A17 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.78 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1639
304.7 IPS |
|
|
Image Classification (HP)
|
100% |
11448
2.13 KIPS |
|
|
Image Classification (Q)
|
97% |
14710
2.75 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1559
25.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
14153
229.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
18540
300.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
7575
8.84 IPS |
|
|
Pose Estimation (HP)
|
100% |
103506
120.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
202362
237.2 IPS |
|
|
Object Detection (SP)
|
100% |
1724
136.7 IPS |
|
|
Object Detection (HP)
|
100% |
13671
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
18370
1.47 KIPS |
|
|
Face Detection (SP)
|
100% |
2785
33.1 IPS |
|
|
Face Detection (HP)
|
100% |
33052
392.7 IPS |
|
|
Face Detection (Q)
|
100% |
46667
554.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6656
51.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
77974
600.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
127387
996.0 IPS |
|
|
Style Transfer (SP)
|
100% |
20920
26.9 IPS |
|
|
Style Transfer (HP)
|
100% |
202592
260.4 IPS |
|
|
Style Transfer (Q)
|
96% |
247639
319.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4882
180.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34061
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57474
2.12 KIPS |
|
|
Text Classification (SP)
|
100% |
3179
4.24 KIPS |
|
|
Text Classification (HP)
|
100% |
3075
4.10 KIPS |
|
|
Text Classification (Q)
|
93% |
2926
3.93 KIPS |
|
|
Machine Translation (SP)
|
100% |
3069
52.9 IPS |
|
|
Machine Translation (HP)
|
100% |
6485
111.7 IPS |
|
|
Machine Translation (Q)
|
98% |
7535
130.2 IPS |
