Mac mini (2023)
Geekbench AI Score
3525
Single Precision Score
6029
Half Precision Score
4912
Quantized Score
Geekbench AI 1.2.0 for macOS AArch64
Result Information
| User | Chris Sack |
| Upload Date | January 25 2025 10:31 PM |
| Views | 16 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 |
| System Information | |
|---|---|
| Operating System | macOS 15.2 (Build 24C101) |
| 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 |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1413
262.7 IPS |
|
|
Image Classification (HP)
|
100% |
2543
472.9 IPS |
|
|
Image Classification (Q)
|
96% |
1785
333.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1552
25.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2478
40.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
2888
46.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
6924
8.08 IPS |
|
|
Pose Estimation (HP)
|
100% |
15028
17.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
13078
15.3 IPS |
|
|
Object Detection (SP)
|
100% |
1580
125.3 IPS |
|
|
Object Detection (HP)
|
97% |
2925
232.8 IPS |
|
|
Object Detection (Q)
|
94% |
2106
167.9 IPS |
|
|
Face Detection (SP)
|
100% |
3173
37.7 IPS |
|
|
Face Detection (HP)
|
100% |
6212
73.8 IPS |
|
|
Face Detection (Q)
|
100% |
3597
42.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
5889
45.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
11913
92.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
8262
64.6 IPS |
|
|
Style Transfer (SP)
|
100% |
19059
24.5 IPS |
|
|
Style Transfer (HP)
|
100% |
28690
36.9 IPS |
|
|
Style Transfer (Q)
|
96% |
24051
31.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4168
153.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4872
179.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3666
135.4 IPS |
|
|
Text Classification (SP)
|
100% |
2271
3.03 KIPS |
|
|
Text Classification (HP)
|
100% |
3802
5.08 KIPS |
|
|
Text Classification (Q)
|
93% |
3777
5.07 KIPS |
|
|
Machine Translation (SP)
|
100% |
3670
63.2 IPS |
|
|
Machine Translation (HP)
|
98% |
5829
100.7 IPS |
|
|
Machine Translation (Q)
|
98% |
5820
100.6 IPS |
