MacBook Pro (16-inch Late 2019)
Geekbench ML Score
1876
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AVX2
Result Information
| User | so1szk |
| Upload Date | August 16 2024 09:20 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.6.1 (Build 23G93) |
| Model | MacBook Pro (16-inch Late 2019) |
| Model ID | MacBookPro16,1 |
| Motherboard | Apple Inc. Mac-E1008331FDC96864 MacBookPro16,1 |
| CPU Information | |
|---|---|
| Name | Intel Core i7-9750H |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 10 |
| Base Frequency | 2.60 GHz |
| Cluster 1 | 6 Cores |
| L1 Instruction Cache | 32.0 KB x 6 |
| L1 Data Cache | 32.0 KB x 6 |
| L2 Cache | 256 KB x 6 |
| L3 Cache | 12.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Transfer Rate | 2667 MT/s |
| Type | DDR4 |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1944
363.8 IPS |
|
|
Image Classification (F16)
|
100% |
1899
355.3 IPS |
|
|
Image Classification (I8)
|
99% |
1855
347.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
210
3.50 IPS |
|
|
Image Segmentation (F16)
|
100% |
198
3.31 IPS |
|
|
Image Segmentation (I8)
|
100% |
184
3.08 IPS |
|
|
Pose Estimation (F32)
|
100% |
13193
16.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
14165
17.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
14105
17.1 IPS |
|
|
Object Detection (F32)
|
100% |
905
67.6 IPS |
|
|
Object Detection (F16)
|
100% |
892
66.6 IPS |
|
|
Object Detection (I8)
|
97% |
884
66.0 IPS |
|
|
Face Detection (F32)
|
100% |
6376
75.8 IPS |
|
|
Face Detection (F16)
|
98% |
6828
81.2 IPS |
|
|
Face Detection (I8)
|
97% |
7058
83.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
8486
65.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
8694
67.4 IPS |
|
|
Depth Estimation (I8)
|
37% |
8286
64.3 IPS |
|
|
Style Transfer (F32)
|
100% |
25188
33.1 IPS |
|
|
Style Transfer (F16)
|
100% |
25282
33.3 IPS |
|
|
Style Transfer (I8)
|
100% |
25397
33.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2145
76.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
3733
133.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
3224
115.1 IPS |
|
|
Text Classification (F32)
|
100% |
147
211.1 IPS |
|
|
Text Classification (F16)
|
100% |
183
263.6 IPS |
|
|
Text Classification (I8)
|
96% |
161
231.0 IPS |
|
|
Machine Translation (F32)
|
100% |
244
4.48 IPS |
|
|
Machine Translation (F16)
|
100% |
138
2.54 IPS |
|
|
Machine Translation (I8)
|
99% |
141
2.59 IPS |
