MacBook Pro (16-inch, Nov 2023)
Geekbench ML Score
9289
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 16 2024 04:41 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.6.1 (Build 23G93) |
| Model | MacBook Pro (16-inch, Nov 2023) |
| Model ID | Mac15,11 |
| Motherboard | Mac15,11 |
| CPU Information | |
|---|---|
| Name | Apple M3 Max |
| Topology | 1 Processor, 14 Cores |
| Identifier | Apple M3 Max |
| Base Frequency | 4.04 GHz |
| Cluster 1 | 10 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 | 36.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
6319
1.18 KIPS |
|
|
Image Classification (F16)
|
100% |
7337
1.37 KIPS |
|
|
Image Classification (I8)
|
99% |
6050
1.13 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2859
47.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
2751
45.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
2855
47.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
62492
75.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
65619
79.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
63839
77.3 IPS |
|
|
Object Detection (F32)
|
100% |
4891
365.2 IPS |
|
|
Object Detection (F16)
|
100% |
5138
383.6 IPS |
|
|
Object Detection (I8)
|
97% |
4761
355.5 IPS |
|
|
Face Detection (F32)
|
100% |
20888
248.4 IPS |
|
|
Face Detection (F16)
|
98% |
24063
286.1 IPS |
|
|
Face Detection (I8)
|
97% |
22098
262.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
30941
239.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
33147
257.1 IPS |
|
|
Depth Estimation (I8)
|
37% |
32657
253.3 IPS |
|
|
Style Transfer (F32)
|
100% |
131267
172.7 IPS |
|
|
Style Transfer (F16)
|
100% |
148119
194.8 IPS |
|
|
Style Transfer (I8)
|
100% |
141641
186.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
10173
363.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
12739
454.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
9502
339.3 IPS |
|
|
Text Classification (F32)
|
100% |
521
749.2 IPS |
|
|
Text Classification (F16)
|
100% |
718
1.03 KIPS |
|
|
Text Classification (I8)
|
96% |
641
921.5 IPS |
|
|
Machine Translation (F32)
|
100% |
1256
23.1 IPS |
|
|
Machine Translation (F16)
|
99% |
1199
22.1 IPS |
|
|
Machine Translation (I8)
|
99% |
1220
22.4 IPS |
