Mac mini (2023)
Geekbench AI Score
7631
Single Precision Score
8532
Half Precision Score
7953
Quantized Score
Geekbench AI 1.5.0 for macOS AArch64
Result Information
| User | macbookjoe |
| Upload Date | September 15 2025 07:21 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 | 3.48 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
3707
689.3 IPS |
|
|
Image Classification (HP)
|
100% |
3653
679.4 IPS |
|
|
Image Classification (Q)
|
96% |
3465
647.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
5749
93.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
5898
95.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
5622
91.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
24495
28.6 IPS |
|
|
Pose Estimation (HP)
|
100% |
26832
31.3 IPS |
|
|
Pose Estimation (Q)
|
96% |
25973
30.4 IPS |
|
|
Object Detection (SP)
|
100% |
3529
279.9 IPS |
|
|
Object Detection (HP)
|
100% |
3770
299.0 IPS |
|
|
Object Detection (Q)
|
92% |
3275
261.4 IPS |
|
|
Face Detection (SP)
|
100% |
10325
122.7 IPS |
|
|
Face Detection (HP)
|
100% |
12208
145.1 IPS |
|
|
Face Detection (Q)
|
100% |
9880
117.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
16786
129.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
18164
139.9 IPS |
|
|
Depth Estimation (Q)
|
86% |
16706
130.5 IPS |
|
|
Style Transfer (SP)
|
100% |
42570
54.7 IPS |
|
|
Style Transfer (HP)
|
100% |
49185
63.2 IPS |
|
|
Style Transfer (Q)
|
96% |
47772
61.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
10329
381.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
10376
383.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
9109
336.3 IPS |
|
|
Text Classification (SP)
|
100% |
2335
3.12 KIPS |
|
|
Text Classification (HP)
|
100% |
3861
5.15 KIPS |
|
|
Text Classification (Q)
|
93% |
3853
5.17 KIPS |
|
|
Machine Translation (SP)
|
100% |
2045
35.2 IPS |
|
|
Machine Translation (HP)
|
100% |
2148
37.0 IPS |
|
|
Machine Translation (Q)
|
98% |
2210
38.2 IPS |
