iPhone 15 Pro Max
Geekbench AI Score
3936
Single Precision Score
24438
Half Precision Score
33912
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 17 2024 08:03 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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% |
1723
320.4 IPS |
|
|
Image Classification (HP)
|
100% |
10812
2.01 KIPS |
|
|
Image Classification (Q)
|
97% |
16224
3.03 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1629
26.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
12971
210.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
16028
259.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
7830
9.14 IPS |
|
|
Pose Estimation (HP)
|
100% |
106293
124.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
203538
238.6 IPS |
|
|
Object Detection (SP)
|
100% |
1778
141.0 IPS |
|
|
Object Detection (HP)
|
100% |
13604
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
19287
1.54 KIPS |
|
|
Face Detection (SP)
|
100% |
3134
37.2 IPS |
|
|
Face Detection (HP)
|
100% |
35113
417.2 IPS |
|
|
Face Detection (Q)
|
100% |
49038
582.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
7090
54.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
79009
608.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
127628
997.9 IPS |
|
|
Style Transfer (SP)
|
100% |
20892
26.9 IPS |
|
|
Style Transfer (HP)
|
100% |
204256
262.6 IPS |
|
|
Style Transfer (Q)
|
96% |
246148
317.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4930
182.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34376
1.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57353
2.12 KIPS |
|
|
Text Classification (SP)
|
100% |
3212
4.29 KIPS |
|
|
Text Classification (HP)
|
100% |
3066
4.09 KIPS |
|
|
Text Classification (Q)
|
93% |
3055
4.10 KIPS |
|
|
Machine Translation (SP)
|
100% |
3111
53.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6274
108.1 IPS |
|
|
Machine Translation (Q)
|
98% |
7302
126.2 IPS |
