Mac mini (2023)
Geekbench ML Score
3429
Core ML CPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | January 21 2025 03:47 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.7.2 (Build 23H311) |
| Model | Mac mini (2023) |
| Model ID | Mac14,12 |
| Motherboard | Mac14,12 |
| CPU Information | |
|---|---|
| Name | Apple M2 Pro |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M2 Pro |
| Base Frequency | 3.48 GHz |
| Cluster 1 | 6 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 | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1454
272.1 IPS |
|
|
Image Classification (F16)
|
100% |
1793
335.5 IPS |
|
|
Image Classification (I8)
|
99% |
1813
339.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
874
14.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
868
14.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
863
14.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
6053
7.33 IPS |
|
|
Pose Estimation (F16)
|
100% |
13771
16.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
13795
16.7 IPS |
|
|
Object Detection (F32)
|
100% |
1459
108.9 IPS |
|
|
Object Detection (F16)
|
100% |
1957
146.1 IPS |
|
|
Object Detection (I8)
|
97% |
1466
109.4 IPS |
|
|
Face Detection (F32)
|
100% |
2925
34.8 IPS |
|
|
Face Detection (F16)
|
97% |
4235
50.4 IPS |
|
|
Face Detection (I8)
|
97% |
4267
50.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
5437
42.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
8501
65.9 IPS |
|
|
Depth Estimation (I8)
|
99% |
8315
64.5 IPS |
|
|
Style Transfer (F32)
|
100% |
16532
21.7 IPS |
|
|
Style Transfer (F16)
|
100% |
25772
33.9 IPS |
|
|
Style Transfer (I8)
|
100% |
24967
32.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3763
134.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4828
172.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4985
178.0 IPS |
|
|
Text Classification (F32)
|
100% |
2081
2.99 KIPS |
|
|
Text Classification (F16)
|
100% |
3187
4.58 KIPS |
|
|
Text Classification (I8)
|
96% |
3192
4.59 KIPS |
|
|
Machine Translation (F32)
|
100% |
1115
20.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1504
27.7 IPS |
|
|
Machine Translation (I8)
|
99% |
1098
20.2 IPS |
