Macbook Neo Mac17,5
Geekbench AI Score
4919
Single Precision Score
8332
Half Precision Score
6599
Quantized Score
Geekbench AI 1.7.0 for macOS AArch64
Result Information
| User | Bredbandsbandit |
| Upload Date | April 03 2026 12:15 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | macOS 26.5 (Build 25F5042g) |
| Model | Mac17,5 |
| Model ID | Mac17,5 |
| Motherboard | Mac17,5 |
| CPU Information | |
|---|---|
| Name | Apple A18 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | Apple A18 Pro |
| Base Frequency | 4.04 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2173
404.1 IPS |
|
|
Image Classification (HP)
|
100% |
3506
652.0 IPS |
|
|
Image Classification (Q)
|
96% |
2335
436.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
2064
33.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2968
48.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
3394
55.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
7894
9.21 IPS |
|
|
Pose Estimation (HP)
|
100% |
17422
20.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
15014
17.6 IPS |
|
|
Object Detection (SP)
|
100% |
2419
191.8 IPS |
|
|
Object Detection (HP)
|
97% |
3845
306.1 IPS |
|
|
Object Detection (Q)
|
94% |
2685
214.0 IPS |
|
|
Face Detection (SP)
|
100% |
4368
51.9 IPS |
|
|
Face Detection (HP)
|
100% |
7619
90.5 IPS |
|
|
Face Detection (Q)
|
100% |
4180
49.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
7584
58.4 IPS |
|
|
Depth Estimation (HP)
|
97% |
13739
106.2 IPS |
|
|
Depth Estimation (Q)
|
86% |
9583
74.8 IPS |
|
|
Style Transfer (SP)
|
100% |
20467
26.3 IPS |
|
|
Style Transfer (HP)
|
100% |
38177
49.1 IPS |
|
|
Style Transfer (Q)
|
96% |
31133
40.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4807
177.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
7200
265.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5048
186.4 IPS |
|
|
Text Classification (SP)
|
99% |
6607
8.82 KIPS |
|
|
Text Classification (HP)
|
99% |
10008
13.4 KIPS |
|
|
Text Classification (Q)
|
92% |
9750
13.1 KIPS |
|
|
Machine Translation (SP)
|
100% |
4499
77.5 IPS |
|
|
Machine Translation (HP)
|
98% |
8038
138.9 IPS |
|
|
Machine Translation (Q)
|
98% |
7989
138.1 IPS |
