MacBook Pro (16-inch, 2021)
Geekbench ML Score
6627
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| Upload Date | January 21 2024 02:02 PM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.2.1 (Build 23C71) |
| Model | MacBook Pro (16-inch, 2021) |
| Model ID | MacBookPro18,2 |
| Motherboard | MacBookPro18,2 |
| CPU Information | |
|---|---|
| Name | Apple M1 Max |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M1 Max |
| Base Frequency | 3.22 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 2 Cores |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
4625
865.4 IPS |
|
|
Image Classification (F16)
|
100% |
4378
819.3 IPS |
|
|
Image Classification (I8)
|
99% |
3797
710.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
1576
26.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1569
26.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
1563
26.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
51511
62.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
54317
65.8 IPS |
|
|
Pose Estimation (I8)
|
100% |
52705
63.8 IPS |
|
|
Object Detection (F32)
|
100% |
3409
254.5 IPS |
|
|
Object Detection (F16)
|
100% |
3469
259.0 IPS |
|
|
Object Detection (I8)
|
97% |
2990
223.2 IPS |
|
|
Face Detection (F32)
|
100% |
16944
201.5 IPS |
|
|
Face Detection (F16)
|
97% |
16576
197.1 IPS |
|
|
Face Detection (I8)
|
96% |
15363
182.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
24573
190.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
25576
198.3 IPS |
|
|
Depth Estimation (I8)
|
37% |
22674
175.8 IPS |
|
|
Style Transfer (F32)
|
100% |
86466
113.7 IPS |
|
|
Style Transfer (F16)
|
100% |
94646
124.5 IPS |
|
|
Style Transfer (I8)
|
100% |
93089
122.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
11550
412.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
11252
401.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
10422
372.2 IPS |
|
|
Text Classification (F32)
|
100% |
458
658.9 IPS |
|
|
Text Classification (F16)
|
100% |
496
712.1 IPS |
|
|
Text Classification (I8)
|
96% |
536
770.2 IPS |
|
|
Machine Translation (F32)
|
100% |
756
13.9 IPS |
|
|
Machine Translation (F16)
|
100% |
732
13.5 IPS |
|
|
Machine Translation (I8)
|
99% |
660
12.2 IPS |
