Mac mini (2023)
Geekbench ML Score
3383
Core ML CPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | August 15 2024 01:32 PM |
| Views | 10 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.5 (Build 23F79) |
| 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 | 3.46 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% |
1445
270.3 IPS |
|
|
Image Classification (F16)
|
100% |
1880
351.9 IPS |
|
|
Image Classification (I8)
|
99% |
1886
353.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
739
12.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
760
12.7 IPS |
|
|
Image Segmentation (I8)
|
100% |
753
12.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
5731
6.94 IPS |
|
|
Pose Estimation (F16)
|
100% |
13812
16.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
13886
16.8 IPS |
|
|
Object Detection (F32)
|
100% |
1428
106.6 IPS |
|
|
Object Detection (F16)
|
100% |
2013
150.3 IPS |
|
|
Object Detection (I8)
|
97% |
1422
106.2 IPS |
|
|
Face Detection (F32)
|
100% |
2644
31.4 IPS |
|
|
Face Detection (F16)
|
97% |
4128
49.1 IPS |
|
|
Face Detection (I8)
|
97% |
4077
48.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
5130
39.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
8496
65.9 IPS |
|
|
Depth Estimation (I8)
|
99% |
8376
65.0 IPS |
|
|
Style Transfer (F32)
|
100% |
16280
21.4 IPS |
|
|
Style Transfer (F16)
|
100% |
26168
34.4 IPS |
|
|
Style Transfer (I8)
|
100% |
26178
34.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3714
132.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5042
180.1 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5027
179.5 IPS |
|
|
Text Classification (F32)
|
100% |
2109
3.03 KIPS |
|
|
Text Classification (F16)
|
100% |
2963
4.26 KIPS |
|
|
Text Classification (I8)
|
96% |
2976
4.28 KIPS |
|
|
Machine Translation (F32)
|
100% |
1278
23.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1513
27.8 IPS |
|
|
Machine Translation (I8)
|
99% |
1278
23.5 IPS |
