Mac mini (2024)
Geekbench AI Score
4534
Single Precision Score
7538
Half Precision Score
6111
Quantized Score
Geekbench AI 1.3.0 for macOS AArch64
Result Information
| User | CircuitSphere |
| Upload Date | March 19 2025 07:07 AM |
| Views | 17 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M4 |
| System Information | |
|---|---|
| Operating System | macOS 15.3.2 (Build 24D81) |
| Model | Mac mini (2024) |
| Model ID | Mac16,10 |
| Motherboard | Mac16,10 |
| CPU Information | |
|---|---|
| Name | Apple M4 |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M4 |
| Base Frequency | 4.41 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1919
356.9 IPS |
|
|
Image Classification (HP)
|
100% |
3234
601.4 IPS |
|
|
Image Classification (Q)
|
96% |
2293
428.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1988
32.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
3138
50.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
3511
56.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
9531
11.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
18426
21.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
16207
19.0 IPS |
|
|
Object Detection (SP)
|
100% |
2191
173.8 IPS |
|
|
Object Detection (HP)
|
97% |
3641
289.8 IPS |
|
|
Object Detection (Q)
|
94% |
2658
211.9 IPS |
|
|
Face Detection (SP)
|
100% |
3596
42.7 IPS |
|
|
Face Detection (HP)
|
100% |
6745
80.2 IPS |
|
|
Face Detection (Q)
|
100% |
4110
48.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
7997
61.6 IPS |
|
|
Depth Estimation (HP)
|
97% |
14351
110.9 IPS |
|
|
Depth Estimation (Q)
|
86% |
10026
78.3 IPS |
|
|
Style Transfer (SP)
|
100% |
24118
31.0 IPS |
|
|
Style Transfer (HP)
|
100% |
37724
48.5 IPS |
|
|
Style Transfer (Q)
|
96% |
31146
40.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5624
207.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6702
247.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4768
176.1 IPS |
|
|
Text Classification (SP)
|
100% |
3186
4.25 KIPS |
|
|
Text Classification (HP)
|
100% |
5692
7.60 KIPS |
|
|
Text Classification (Q)
|
93% |
5517
7.40 KIPS |
|
|
Machine Translation (SP)
|
100% |
3714
64.0 IPS |
|
|
Machine Translation (HP)
|
98% |
6249
108.0 IPS |
|
|
Machine Translation (Q)
|
98% |
6213
107.4 IPS |
