Mac mini (2024)
Geekbench AI Score
5779
Single Precision Score
8869
Half Precision Score
6876
Quantized Score
Geekbench AI 1.2.0 for macOS AArch64
Result Information
| User | sfoskett |
| Upload Date | December 10 2024 04:54 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M4 Pro |
| System Information | |
|---|---|
| Operating System | macOS 15.1 (Build 24B2082) |
| Model | Mac mini (2024) |
| Model ID | Mac16,11 |
| Motherboard | Mac16,11 |
| CPU Information | |
|---|---|
| Name | Apple M4 Pro |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M4 Pro |
| Base Frequency | 4.51 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 24.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2080
386.9 IPS |
|
|
Image Classification (HP)
|
100% |
3037
564.8 IPS |
|
|
Image Classification (Q)
|
96% |
2202
411.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
2455
39.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
3517
57.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
3936
63.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
18983
22.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
31339
36.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
23584
27.6 IPS |
|
|
Object Detection (SP)
|
100% |
2488
197.4 IPS |
|
|
Object Detection (HP)
|
97% |
3822
304.3 IPS |
|
|
Object Detection (Q)
|
94% |
2666
212.5 IPS |
|
|
Face Detection (SP)
|
100% |
4577
54.4 IPS |
|
|
Face Detection (HP)
|
100% |
7962
94.6 IPS |
|
|
Face Detection (Q)
|
100% |
4608
54.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
8820
68.0 IPS |
|
|
Depth Estimation (HP)
|
97% |
14108
109.1 IPS |
|
|
Depth Estimation (Q)
|
86% |
10007
78.1 IPS |
|
|
Style Transfer (SP)
|
100% |
35203
45.3 IPS |
|
|
Style Transfer (HP)
|
100% |
47456
61.0 IPS |
|
|
Style Transfer (Q)
|
96% |
38548
49.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
7052
260.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
9538
352.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5228
193.0 IPS |
|
|
Text Classification (SP)
|
100% |
2950
3.94 KIPS |
|
|
Text Classification (HP)
|
100% |
5313
7.09 KIPS |
|
|
Text Classification (Q)
|
93% |
5289
7.10 KIPS |
|
|
Machine Translation (SP)
|
100% |
5830
100.4 IPS |
|
|
Machine Translation (HP)
|
98% |
8715
150.6 IPS |
|
|
Machine Translation (Q)
|
98% |
8825
152.5 IPS |
