MacBook Pro (16-inch, Nov 2023)
Geekbench ML Score
10255
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | May 08 2024 09:50 PM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.4.1 (Build 23E224) |
| Model | MacBook Pro (16-inch, Nov 2023) |
| Model ID | Mac15,9 |
| Motherboard | Mac15,9 |
| CPU Information | |
|---|---|
| Name | Apple M3 Max |
| Topology | 1 Processor, 16 Cores |
| Identifier | Apple M3 Max |
| Base Frequency | 4.05 GHz |
| Cluster 1 | 12 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 | 48.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
6759
1.26 KIPS |
|
|
Image Classification (F16)
|
100% |
7115
1.33 KIPS |
|
|
Image Classification (I8)
|
99% |
6602
1.24 KIPS |
|
|
Image Segmentation (F32)
|
100% |
3045
50.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
3051
51.0 IPS |
|
|
Image Segmentation (I8)
|
100% |
3070
51.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
84005
101.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
87982
106.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
83920
101.6 IPS |
|
|
Object Detection (F32)
|
100% |
5127
382.8 IPS |
|
|
Object Detection (F16)
|
100% |
5341
398.8 IPS |
|
|
Object Detection (I8)
|
97% |
5050
377.0 IPS |
|
|
Face Detection (F32)
|
100% |
24068
286.2 IPS |
|
|
Face Detection (F16)
|
98% |
26457
314.6 IPS |
|
|
Face Detection (I8)
|
97% |
24916
296.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
36171
280.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
38117
295.6 IPS |
|
|
Depth Estimation (I8)
|
37% |
36918
286.3 IPS |
|
|
Style Transfer (F32)
|
100% |
166492
219.0 IPS |
|
|
Style Transfer (F16)
|
100% |
174525
229.6 IPS |
|
|
Style Transfer (I8)
|
100% |
175578
231.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
9463
338.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
16737
597.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
10322
368.6 IPS |
|
|
Text Classification (F32)
|
100% |
638
916.8 IPS |
|
|
Text Classification (F16)
|
100% |
713
1.03 KIPS |
|
|
Text Classification (I8)
|
96% |
712
1.02 KIPS |
|
|
Machine Translation (F32)
|
100% |
1102
20.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1113
20.5 IPS |
|
|
Machine Translation (I8)
|
99% |
1026
18.9 IPS |
