iPhone 15 Pro Max
Geekbench ML Score
8923
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 17 2024 12:28 PM |
| Views | 2 |
System Information
| 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 |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 7.48 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1183
221.3 IPS |
|
|
Image Classification (F16)
|
100% |
10107
1.89 KIPS |
|
|
Image Classification (I8)
|
99% |
11557
2.16 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1377
23.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
2228
37.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
2240
37.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
14823
18.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
97806
118.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
99884
121.0 IPS |
|
|
Object Detection (F32)
|
100% |
1516
113.1 IPS |
|
|
Object Detection (F16)
|
100% |
5896
440.2 IPS |
|
|
Object Detection (I8)
|
97% |
1825
136.2 IPS |
|
|
Face Detection (F32)
|
100% |
5884
70.0 IPS |
|
|
Face Detection (F16)
|
97% |
20149
239.6 IPS |
|
|
Face Detection (I8)
|
96% |
20133
239.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
12448
96.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
51218
397.2 IPS |
|
|
Depth Estimation (I8)
|
37% |
52015
403.4 IPS |
|
|
Style Transfer (F32)
|
100% |
29469
38.8 IPS |
|
|
Style Transfer (F16)
|
100% |
129396
170.2 IPS |
|
|
Style Transfer (I8)
|
100% |
134790
177.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7201
257.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
31086
1.11 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
32291
1.15 KIPS |
|
|
Text Classification (F32)
|
100% |
2920
4.20 KIPS |
|
|
Text Classification (F16)
|
100% |
5288
7.60 KIPS |
|
|
Text Classification (I8)
|
96% |
5105
7.34 KIPS |
|
|
Machine Translation (F32)
|
100% |
620
11.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1586
29.2 IPS |
|
|
Machine Translation (I8)
|
99% |
642
11.8 IPS |
