MacBook Pro (14-inch, 2023)
Geekbench ML Score
3493
Core ML CPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| User | aebrownleeiv |
| Upload Date | August 16 2024 06:36 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.6.1 (Build 23G93) |
| Model | MacBook Pro (14-inch, 2023) |
| Model ID | Mac14,5 |
| Motherboard | Mac14,5 |
| CPU Information | |
|---|---|
| Name | Apple M2 Max |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Max |
| Base Frequency | 3.47 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 | 96.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1450
271.3 IPS |
|
|
Image Classification (F16)
|
100% |
1805
337.8 IPS |
|
|
Image Classification (I8)
|
99% |
1798
336.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
892
14.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
889
14.8 IPS |
|
|
Image Segmentation (I8)
|
100% |
884
14.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
5971
7.23 IPS |
|
|
Pose Estimation (F16)
|
100% |
14358
17.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
14401
17.4 IPS |
|
|
Object Detection (F32)
|
100% |
1476
110.2 IPS |
|
|
Object Detection (F16)
|
100% |
1951
145.7 IPS |
|
|
Object Detection (I8)
|
97% |
1442
107.6 IPS |
|
|
Face Detection (F32)
|
100% |
2943
35.0 IPS |
|
|
Face Detection (F16)
|
97% |
4288
51.0 IPS |
|
|
Face Detection (I8)
|
97% |
4228
50.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
5519
42.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
8565
66.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
8531
66.2 IPS |
|
|
Style Transfer (F32)
|
100% |
16371
21.5 IPS |
|
|
Style Transfer (F16)
|
100% |
26128
34.4 IPS |
|
|
Style Transfer (I8)
|
100% |
26127
34.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3823
136.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5061
180.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5013
179.0 IPS |
|
|
Text Classification (F32)
|
100% |
2127
3.06 KIPS |
|
|
Text Classification (F16)
|
100% |
3437
4.94 KIPS |
|
|
Text Classification (I8)
|
96% |
3444
4.95 KIPS |
|
|
Machine Translation (F32)
|
100% |
1148
21.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1543
28.4 IPS |
|
|
Machine Translation (I8)
|
99% |
1129
20.8 IPS |
