Mac17,2
Geekbench AI Score
2912
Single Precision Score
4675
Half Precision Score
3651
Quantized Score
Geekbench AI 1.5.0 for macOS AArch64
Result Information
| Upload Date | December 13 2025 11:51 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M5 |
| System Information | |
|---|---|
| Operating System | macOS 26.2 (Build 25C56) |
| Model | Mac17,2 |
| Model ID | Mac17,2 |
| Motherboard | Mac17,2 |
| CPU Information | |
|---|---|
| Name | Apple M5 |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M5 |
| Base Frequency | 2.22 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1223
227.5 IPS |
|
|
Image Classification (HP)
|
100% |
1933
359.5 IPS |
|
|
Image Classification (Q)
|
96% |
1267
236.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1385
22.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2010
32.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
2022
32.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
6224
7.26 IPS |
|
|
Pose Estimation (HP)
|
100% |
11079
12.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
9455
11.1 IPS |
|
|
Object Detection (SP)
|
100% |
1414
112.1 IPS |
|
|
Object Detection (HP)
|
97% |
2233
177.7 IPS |
|
|
Object Detection (Q)
|
94% |
1543
123.0 IPS |
|
|
Face Detection (SP)
|
100% |
2429
28.9 IPS |
|
|
Face Detection (HP)
|
100% |
4435
52.7 IPS |
|
|
Face Detection (Q)
|
100% |
2467
29.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
4990
38.4 IPS |
|
|
Depth Estimation (HP)
|
97% |
8115
62.7 IPS |
|
|
Depth Estimation (Q)
|
86% |
5577
43.5 IPS |
|
|
Style Transfer (SP)
|
100% |
14569
18.7 IPS |
|
|
Style Transfer (HP)
|
100% |
21596
27.8 IPS |
|
|
Style Transfer (Q)
|
96% |
17643
22.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3264
120.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4004
147.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2790
103.0 IPS |
|
|
Text Classification (SP)
|
100% |
1719
2.29 KIPS |
|
|
Text Classification (HP)
|
99% |
3016
4.03 KIPS |
|
|
Text Classification (Q)
|
93% |
3017
4.05 KIPS |
|
|
Machine Translation (SP)
|
100% |
2974
51.2 IPS |
|
|
Machine Translation (HP)
|
98% |
5535
95.6 IPS |
|
|
Machine Translation (Q)
|
98% |
5524
95.5 IPS |
