Mac mini (2023)
Geekbench ML Score
3497
Core ML CPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | April 26 2024 08:24 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.4 (Build 23E214) |
| Model | Mac mini (2023) |
| Model ID | Mac14,3 |
| Motherboard | Mac14,3 |
| CPU Information | |
|---|---|
| Name | Apple M2 |
| Topology | 1 Processor, 8 Cores |
| Identifier | Apple M2 |
| Base Frequency | 3.48 GHz |
| Cluster 1 | 4 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 | 8.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1501
280.9 IPS |
|
|
Image Classification (F16)
|
100% |
1910
357.4 IPS |
|
|
Image Classification (I8)
|
99% |
1913
357.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
802
13.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
821
13.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
816
13.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
5935
7.19 IPS |
|
|
Pose Estimation (F16)
|
100% |
14094
17.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
14097
17.1 IPS |
|
|
Object Detection (F32)
|
100% |
1502
112.1 IPS |
|
|
Object Detection (F16)
|
100% |
2058
153.6 IPS |
|
|
Object Detection (I8)
|
97% |
1502
112.2 IPS |
|
|
Face Detection (F32)
|
100% |
2867
34.1 IPS |
|
|
Face Detection (F16)
|
97% |
4433
52.7 IPS |
|
|
Face Detection (I8)
|
97% |
4376
52.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
5429
42.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
8785
68.1 IPS |
|
|
Depth Estimation (I8)
|
99% |
8781
68.1 IPS |
|
|
Style Transfer (F32)
|
100% |
17011
22.4 IPS |
|
|
Style Transfer (F16)
|
100% |
26619
35.0 IPS |
|
|
Style Transfer (I8)
|
100% |
26637
35.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3829
136.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4979
177.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5042
180.1 IPS |
|
|
Text Classification (F32)
|
100% |
2094
3.01 KIPS |
|
|
Text Classification (F16)
|
100% |
2951
4.24 KIPS |
|
|
Text Classification (I8)
|
96% |
2939
4.22 KIPS |
|
|
Machine Translation (F32)
|
100% |
1295
23.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1576
29.0 IPS |
|
|
Machine Translation (I8)
|
99% |
1277
23.5 IPS |
