MacBook Pro (16-inch, 2023)
Geekbench ML Score
11408
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 15 2024 05:18 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 15.0 (Build 24A5320a) |
| Model | MacBook Pro (16-inch, 2023) |
| Model ID | Mac14,6 |
| Motherboard | Mac14,6 |
| CPU Information | |
|---|---|
| Name | Apple M2 Max |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Max |
| Base Frequency | 3.64 GHz |
| Cluster 1 | 8 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 | 64.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
5589
1.05 KIPS |
|
|
Image Classification (F16)
|
100% |
10973
2.05 KIPS |
|
|
Image Classification (I8)
|
99% |
12036
2.25 KIPS |
|
|
Image Segmentation (F32)
|
100% |
2230
37.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
2241
37.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
2231
37.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
72726
88.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
96017
116.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
95280
115.4 IPS |
|
|
Object Detection (F32)
|
100% |
3669
273.9 IPS |
|
|
Object Detection (F16)
|
100% |
4556
340.1 IPS |
|
|
Object Detection (I8)
|
97% |
3208
239.5 IPS |
|
|
Face Detection (F32)
|
100% |
17674
210.1 IPS |
|
|
Face Detection (F16)
|
97% |
20536
244.2 IPS |
|
|
Face Detection (I8)
|
96% |
19123
227.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
28989
224.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
45504
352.9 IPS |
|
|
Depth Estimation (I8)
|
37% |
48927
379.4 IPS |
|
|
Style Transfer (F32)
|
100% |
117254
154.2 IPS |
|
|
Style Transfer (F16)
|
100% |
139915
184.0 IPS |
|
|
Style Transfer (I8)
|
100% |
136937
180.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
10306
368.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
28671
1.02 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
29217
1.04 KIPS |
|
|
Text Classification (F32)
|
100% |
2084
2.99 KIPS |
|
|
Text Classification (F16)
|
100% |
3099
4.45 KIPS |
|
|
Text Classification (I8)
|
96% |
3392
4.87 KIPS |
|
|
Machine Translation (F32)
|
100% |
1011
18.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1092
20.1 IPS |
|
|
Machine Translation (I8)
|
99% |
845
15.6 IPS |
