iPhone 15 Pro Max
Geekbench AI Score
4003
Single Precision Score
24122
Half Precision Score
32316
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 17 2024 06:14 AM |
| 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% |
1713
318.5 IPS |
|
|
Image Classification (HP)
|
100% |
11074
2.06 KIPS |
|
|
Image Classification (Q)
|
97% |
15243
2.84 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1625
26.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
12903
209.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
16073
260.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
8359
9.75 IPS |
|
|
Pose Estimation (HP)
|
100% |
106530
124.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
204443
239.6 IPS |
|
|
Object Detection (SP)
|
100% |
1809
143.5 IPS |
|
|
Object Detection (HP)
|
100% |
13579
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
19259
1.54 KIPS |
|
|
Face Detection (SP)
|
100% |
3191
37.9 IPS |
|
|
Face Detection (HP)
|
100% |
34418
409.0 IPS |
|
|
Face Detection (Q)
|
100% |
49409
587.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
7270
56.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
78670
606.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
129284
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
21666
27.9 IPS |
|
|
Style Transfer (HP)
|
100% |
203782
262.0 IPS |
|
|
Style Transfer (Q)
|
96% |
246517
318.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5026
185.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34486
1.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55976
2.07 KIPS |
|
|
Text Classification (SP)
|
100% |
3192
4.26 KIPS |
|
|
Text Classification (HP)
|
100% |
2774
3.70 KIPS |
|
|
Text Classification (Q)
|
93% |
1953
2.62 KIPS |
|
|
Machine Translation (SP)
|
100% |
3118
53.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6116
105.4 IPS |
|
|
Machine Translation (Q)
|
98% |
7480
129.3 IPS |
