Mac mini (2023)
Geekbench AI Score
7682
Single Precision Score
8659
Half Precision Score
7955
Quantized Score
Geekbench AI 1.5.0 for macOS AArch64
Result Information
| User | DaMoisture |
| Upload Date | September 12 2025 12:03 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Apple M2 |
| System Information | |
|---|---|
| Operating System | macOS 15.6.1 (Build 24G90) |
| 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 | 3.49 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
3741
695.7 IPS |
|
|
Image Classification (HP)
|
100% |
3720
691.9 IPS |
|
|
Image Classification (Q)
|
96% |
3488
651.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
5717
92.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
5965
96.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
5620
91.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
24589
28.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
26775
31.2 IPS |
|
|
Pose Estimation (Q)
|
96% |
26046
30.5 IPS |
|
|
Object Detection (SP)
|
100% |
3648
289.4 IPS |
|
|
Object Detection (HP)
|
100% |
3765
298.6 IPS |
|
|
Object Detection (Q)
|
92% |
3403
271.6 IPS |
|
|
Face Detection (SP)
|
100% |
10408
123.7 IPS |
|
|
Face Detection (HP)
|
100% |
12125
144.1 IPS |
|
|
Face Detection (Q)
|
100% |
9946
118.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
16948
130.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
18194
140.2 IPS |
|
|
Depth Estimation (Q)
|
86% |
16697
130.4 IPS |
|
|
Style Transfer (SP)
|
100% |
42098
54.1 IPS |
|
|
Style Transfer (HP)
|
100% |
49293
63.4 IPS |
|
|
Style Transfer (Q)
|
96% |
47775
61.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
10031
370.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
10470
386.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
8911
329.0 IPS |
|
|
Text Classification (SP)
|
100% |
2390
3.19 KIPS |
|
|
Text Classification (HP)
|
100% |
3925
5.24 KIPS |
|
|
Text Classification (Q)
|
93% |
3889
5.22 KIPS |
|
|
Machine Translation (SP)
|
100% |
2096
36.1 IPS |
|
|
Machine Translation (HP)
|
100% |
2373
40.9 IPS |
|
|
Machine Translation (Q)
|
98% |
2125
36.7 IPS |
