Mac mini (2023)
Geekbench ML Score
3411
Core ML CPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | May 08 2024 07:29 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.4.1 (Build 23E224) |
| 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 | 3.45 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 | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1435
268.5 IPS |
|
|
Image Classification (F16)
|
100% |
1763
329.9 IPS |
|
|
Image Classification (I8)
|
99% |
1758
329.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
866
14.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
857
14.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
870
14.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
5869
7.11 IPS |
|
|
Pose Estimation (F16)
|
100% |
13173
16.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
13923
16.9 IPS |
|
|
Object Detection (F32)
|
100% |
1418
105.8 IPS |
|
|
Object Detection (F16)
|
100% |
1924
143.6 IPS |
|
|
Object Detection (I8)
|
97% |
1441
107.6 IPS |
|
|
Face Detection (F32)
|
100% |
2870
34.1 IPS |
|
|
Face Detection (F16)
|
97% |
4242
50.4 IPS |
|
|
Face Detection (I8)
|
97% |
4265
50.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
5363
41.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
8484
65.8 IPS |
|
|
Depth Estimation (I8)
|
99% |
8416
65.3 IPS |
|
|
Style Transfer (F32)
|
100% |
16246
21.4 IPS |
|
|
Style Transfer (F16)
|
100% |
25498
33.5 IPS |
|
|
Style Transfer (I8)
|
100% |
25505
33.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3835
137.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4898
174.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4903
175.1 IPS |
|
|
Text Classification (F32)
|
100% |
2064
2.97 KIPS |
|
|
Text Classification (F16)
|
100% |
3213
4.62 KIPS |
|
|
Text Classification (I8)
|
96% |
3253
4.67 KIPS |
|
|
Machine Translation (F32)
|
100% |
1127
20.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1516
27.9 IPS |
|
|
Machine Translation (I8)
|
99% |
1120
20.6 IPS |
