iPhone 15 Pro Max
Geekbench AI Score
3920
Single Precision Score
24335
Half Precision Score
33587
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 17 2024 01:13 PM |
| Views | 2 |
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% |
1726
320.9 IPS |
|
|
Image Classification (HP)
|
100% |
10727
1.99 KIPS |
|
|
Image Classification (Q)
|
97% |
14970
2.79 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1617
26.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
12884
208.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
15996
259.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
7800
9.10 IPS |
|
|
Pose Estimation (HP)
|
100% |
106797
124.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
203924
239.0 IPS |
|
|
Object Detection (SP)
|
100% |
1778
141.0 IPS |
|
|
Object Detection (HP)
|
100% |
13570
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
19229
1.54 KIPS |
|
|
Face Detection (SP)
|
100% |
3177
37.8 IPS |
|
|
Face Detection (HP)
|
100% |
33677
400.2 IPS |
|
|
Face Detection (Q)
|
100% |
49097
583.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
7042
54.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
78937
608.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
129552
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
20629
26.5 IPS |
|
|
Style Transfer (HP)
|
100% |
202120
259.8 IPS |
|
|
Style Transfer (Q)
|
96% |
247123
318.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4837
178.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34704
1.28 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55135
2.04 KIPS |
|
|
Text Classification (SP)
|
100% |
3189
4.26 KIPS |
|
|
Text Classification (HP)
|
100% |
3091
4.13 KIPS |
|
|
Text Classification (Q)
|
93% |
3123
4.19 KIPS |
|
|
Machine Translation (SP)
|
100% |
3112
53.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6309
108.7 IPS |
|
|
Machine Translation (Q)
|
98% |
7190
124.2 IPS |
