iPhone 15 Pro Max
Geekbench AI Score
3921
Single Precision Score
24672
Half Precision Score
33946
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 17 2024 06:04 AM |
| 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% |
1704
316.8 IPS |
|
|
Image Classification (HP)
|
100% |
11123
2.07 KIPS |
|
|
Image Classification (Q)
|
97% |
15436
2.88 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1592
25.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
12873
208.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
16140
261.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
7713
9.00 IPS |
|
|
Pose Estimation (HP)
|
100% |
105813
123.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
203198
238.2 IPS |
|
|
Object Detection (SP)
|
100% |
1780
141.2 IPS |
|
|
Object Detection (HP)
|
100% |
13740
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
19088
1.53 KIPS |
|
|
Face Detection (SP)
|
100% |
3181
37.8 IPS |
|
|
Face Detection (HP)
|
100% |
34409
408.9 IPS |
|
|
Face Detection (Q)
|
100% |
49633
589.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
7077
54.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
79125
609.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
129795
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
20919
26.9 IPS |
|
|
Style Transfer (HP)
|
100% |
203211
261.2 IPS |
|
|
Style Transfer (Q)
|
96% |
246296
317.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4923
181.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34148
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55527
2.05 KIPS |
|
|
Text Classification (SP)
|
100% |
3192
4.26 KIPS |
|
|
Text Classification (HP)
|
100% |
3243
4.33 KIPS |
|
|
Text Classification (Q)
|
93% |
3233
4.34 KIPS |
|
|
Machine Translation (SP)
|
100% |
3122
53.8 IPS |
|
|
Machine Translation (HP)
|
100% |
6552
112.9 IPS |
|
|
Machine Translation (Q)
|
98% |
7384
127.6 IPS |
