Mac mini (2023)
Geekbench AI Score
7629
Single Precision Score
8534
Half Precision Score
8000
Quantized Score
Geekbench AI 1.6.0 for macOS AArch64
Result Information
| User | Birkin |
| Upload Date | January 13 2026 03:48 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Apple M2 |
| System Information | |
|---|---|
| Operating System | macOS 26.2 (Build 25C56) |
| 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% |
3759
699.0 IPS |
|
|
Image Classification (HP)
|
100% |
3648
678.4 IPS |
|
|
Image Classification (Q)
|
96% |
3411
637.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
5782
93.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
5957
96.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
5699
92.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
24726
28.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
26726
31.2 IPS |
|
|
Pose Estimation (Q)
|
96% |
26065
30.5 IPS |
|
|
Object Detection (SP)
|
100% |
3573
283.4 IPS |
|
|
Object Detection (HP)
|
100% |
3642
288.9 IPS |
|
|
Object Detection (Q)
|
92% |
3483
278.0 IPS |
|
|
Face Detection (SP)
|
100% |
10501
124.8 IPS |
|
|
Face Detection (HP)
|
100% |
12102
143.8 IPS |
|
|
Face Detection (Q)
|
100% |
10144
120.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
16892
130.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
18252
140.6 IPS |
|
|
Depth Estimation (Q)
|
86% |
16848
131.6 IPS |
|
|
Style Transfer (SP)
|
100% |
42188
54.2 IPS |
|
|
Style Transfer (HP)
|
100% |
49226
63.3 IPS |
|
|
Style Transfer (Q)
|
96% |
47725
61.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
9885
365.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
10280
379.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
8945
330.3 IPS |
|
|
Text Classification (SP)
|
100% |
2309
3.08 KIPS |
|
|
Text Classification (HP)
|
99% |
4016
5.36 KIPS |
|
|
Text Classification (Q)
|
93% |
3996
5.36 KIPS |
|
|
Machine Translation (SP)
|
100% |
2037
35.1 IPS |
|
|
Machine Translation (HP)
|
100% |
2159
37.2 IPS |
|
|
Machine Translation (Q)
|
98% |
2088
36.1 IPS |
