iPhone 11 Pro Max
Geekbench ML Score
1878
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | January 17 2025 09:49 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.0.2 |
| Model | iPhone 11 Pro Max |
| Model ID | iPhone12,5 |
| Motherboard | D431AP |
| CPU Information | |
|---|---|
| Name | Apple A13 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 2.66 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 96.0 KB x 1 |
| L1 Data Cache | 48.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 3.66 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
288
53.9 IPS |
|
|
Image Classification (F16)
|
100% |
2720
508.9 IPS |
|
|
Image Classification (I8)
|
99% |
2713
507.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
296
4.95 IPS |
|
|
Image Segmentation (F16)
|
100% |
489
8.17 IPS |
|
|
Image Segmentation (I8)
|
100% |
488
8.16 IPS |
|
|
Pose Estimation (F32)
|
100% |
2272
2.75 IPS |
|
|
Pose Estimation (F16)
|
100% |
25838
31.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
26094
31.6 IPS |
|
|
Object Detection (F32)
|
100% |
562
41.9 IPS |
|
|
Object Detection (F16)
|
100% |
1005
75.0 IPS |
|
|
Object Detection (I8)
|
97% |
579
43.3 IPS |
|
|
Face Detection (F32)
|
100% |
2463
29.3 IPS |
|
|
Face Detection (F16)
|
97% |
4298
51.1 IPS |
|
|
Face Detection (I8)
|
96% |
4257
50.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
2669
20.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
24238
188.0 IPS |
|
|
Depth Estimation (I8)
|
99% |
23639
183.3 IPS |
|
|
Style Transfer (F32)
|
24% |
6054
7.96 IPS |
|
|
Style Transfer (F16)
|
100% |
17209
22.6 IPS |
|
|
Style Transfer (I8)
|
100% |
17417
22.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1409
50.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5178
184.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5121
182.9 IPS |
|
|
Text Classification (F32)
|
100% |
249
358.1 IPS |
|
|
Text Classification (F16)
|
100% |
324
465.8 IPS |
|
|
Text Classification (I8)
|
96% |
325
466.8 IPS |
|
|
Machine Translation (F32)
|
100% |
288
5.30 IPS |
|
|
Machine Translation (F16)
|
100% |
206
3.80 IPS |
|
|
Machine Translation (I8)
|
99% |
298
5.48 IPS |
