Mac mini (2023)
Geekbench ML Score
9730
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| User | tifreitas |
| Upload Date | November 06 2024 08:42 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 15.2 (Build 24C5073e) |
| 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 | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
3280
613.8 IPS |
|
|
Image Classification (F16)
|
100% |
11588
2.17 KIPS |
|
|
Image Classification (I8)
|
99% |
13536
2.53 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1353
22.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
2007
33.5 IPS |
|
|
Image Segmentation (I8)
|
100% |
1947
32.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
23406
28.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
96970
117.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
98539
119.3 IPS |
|
|
Object Detection (F32)
|
100% |
2859
213.4 IPS |
|
|
Object Detection (F16)
|
100% |
5384
402.0 IPS |
|
|
Object Detection (I8)
|
97% |
1913
142.8 IPS |
|
|
Face Detection (F32)
|
100% |
8903
105.9 IPS |
|
|
Face Detection (F16)
|
97% |
19789
235.3 IPS |
|
|
Face Detection (I8)
|
96% |
19844
236.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
16161
125.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
54900
425.7 IPS |
|
|
Depth Estimation (I8)
|
37% |
51363
398.3 IPS |
|
|
Style Transfer (F32)
|
100% |
40742
53.6 IPS |
|
|
Style Transfer (F16)
|
100% |
149843
197.1 IPS |
|
|
Style Transfer (I8)
|
100% |
151907
199.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
8008
286.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
35857
1.28 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
35952
1.28 KIPS |
|
|
Text Classification (F32)
|
100% |
2021
2.91 KIPS |
|
|
Text Classification (F16)
|
100% |
3334
4.79 KIPS |
|
|
Text Classification (I8)
|
96% |
3343
4.80 KIPS |
|
|
Machine Translation (F32)
|
100% |
716
13.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1408
25.9 IPS |
|
|
Machine Translation (I8)
|
99% |
710
13.1 IPS |
