MacBook Pro (16-inch, Nov 2023)
Geekbench AI Score
4408
Single Precision Score
32296
Half Precision Score
35036
Quantized Score
Geekbench AI 1.3.0 for macOS AArch64
Result Information
| User | beret |
| Upload Date | April 09 2025 01:06 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple M3 Max |
| System Information | |
|---|---|
| Operating System | macOS 15.4 (Build 24E248) |
| Model | MacBook Pro (16-inch, Nov 2023) |
| Model ID | Mac15,11 |
| Motherboard | Mac15,11 |
| CPU Information | |
|---|---|
| Name | Apple M3 Max |
| Topology | 1 Processor, 14 Cores |
| Identifier | Apple M3 Max |
| Base Frequency | 3.86 GHz |
| Cluster 1 | 10 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 96.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1518
282.3 IPS |
|
|
Image Classification (HP)
|
100% |
16525
3.07 KIPS |
|
|
Image Classification (Q)
|
97% |
17814
3.32 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1842
29.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
22021
357.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
26655
432.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
16115
18.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
119940
139.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
119064
139.6 IPS |
|
|
Object Detection (SP)
|
100% |
1974
156.6 IPS |
|
|
Object Detection (HP)
|
100% |
20025
1.59 KIPS |
|
|
Object Detection (Q)
|
91% |
19655
1.57 KIPS |
|
|
Face Detection (SP)
|
100% |
4110
48.8 IPS |
|
|
Face Detection (HP)
|
100% |
35859
426.1 IPS |
|
|
Face Detection (Q)
|
100% |
42891
509.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
7276
56.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
106665
821.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
128671
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
29505
37.9 IPS |
|
|
Style Transfer (HP)
|
100% |
221201
284.4 IPS |
|
|
Style Transfer (Q)
|
96% |
211750
273.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5807
214.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
43481
1.61 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
53775
1.99 KIPS |
|
|
Text Classification (SP)
|
100% |
2788
3.72 KIPS |
|
|
Text Classification (HP)
|
100% |
5064
6.76 KIPS |
|
|
Text Classification (Q)
|
93% |
5017
6.73 KIPS |
|
|
Machine Translation (SP)
|
100% |
2181
37.6 IPS |
|
|
Machine Translation (HP)
|
98% |
7582
131.0 IPS |
|
|
Machine Translation (Q)
|
98% |
7957
137.5 IPS |
